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1.  Magnetic Resonance Imaging Research in Sub-Saharan Africa: Challenges and Satellite-Based Networking Implementation 
As part of an NIH-funded study of malaria pathogenesis, a magnetic resonance (MR) imaging research facility was established in Blantyre, Malaŵi to enhance the clinical characterization of pediatric patients with cerebral malaria through application of neurological MR methods. The research program requires daily transmission of MR studies to Michigan State University (MSU) for clinical research interpretation and quantitative post-processing. An intercontinental satellite-based network was implemented for transmission of MR image data in Digital Imaging and Communications in Medicine (DICOM) format, research data collection, project communications, and remote systems administration. Satellite Internet service costs limited the bandwidth to symmetrical 384 kbit/s. DICOM routers deployed at both the Malaŵi MRI facility and MSU manage the end-to-end encrypted compressed data transmission. Network performance between DICOM routers was measured while transmitting both mixed clinical MR studies and synthetic studies. Effective network latency averaged 715 ms. Within a mix of clinical MR studies, the average transmission time for a 256 × 256 image was ~2.25 and ~6.25 s for a 512 × 512 image. Using synthetic studies of 1,000 duplicate images, the interquartile range for 256 × 256 images was [2.30, 2.36] s and [5.94, 6.05] s for 512 × 512 images. Transmission of clinical MRI studies between the DICOM routers averaged 9.35 images per minute, representing an effective channel utilization of ~137% of the 384-kbit/s satellite service as computed using uncompressed image file sizes (including the effects of image compression, protocol overhead, channel latency, etc.). Power unreliability was the primary cause of interrupted operations in the first year, including an outage exceeding 10 days.
doi:10.1007/s10278-010-9323-4
PMCID: PMC3033988  PMID: 20714916
Magnetic resonance imaging; computer networks; image distribution; wide area network (WAN); brain imaging; satellite-based networks; sub-Saharan Africa; DICOM router
2.  Magnetic Resonance Imaging Research in Sub-Saharan Africa: Challenges and Satellite-Based Networking Implementation 
Journal of Digital Imaging  2010;24(4):729-738.
As part of an NIH-funded study of malaria pathogenesis, a magnetic resonance (MR) imaging research facility was established in Blantyre, Malaŵi to enhance the clinical characterization of pediatric patients with cerebral malaria through application of neurological MR methods. The research program requires daily transmission of MR studies to Michigan State University (MSU) for clinical research interpretation and quantitative post-processing. An intercontinental satellite-based network was implemented for transmission of MR image data in Digital Imaging and Communications in Medicine (DICOM) format, research data collection, project communications, and remote systems administration. Satellite Internet service costs limited the bandwidth to symmetrical 384 kbit/s. DICOM routers deployed at both the Malaŵi MRI facility and MSU manage the end-to-end encrypted compressed data transmission. Network performance between DICOM routers was measured while transmitting both mixed clinical MR studies and synthetic studies. Effective network latency averaged 715 ms. Within a mix of clinical MR studies, the average transmission time for a 256 × 256 image was ~2.25 and ~6.25 s for a 512 × 512 image. Using synthetic studies of 1,000 duplicate images, the interquartile range for 256 × 256 images was [2.30, 2.36] s and [5.94, 6.05] s for 512 × 512 images. Transmission of clinical MRI studies between the DICOM routers averaged 9.35 images per minute, representing an effective channel utilization of ~137% of the 384-kbit/s satellite service as computed using uncompressed image file sizes (including the effects of image compression, protocol overhead, channel latency, etc.). Power unreliability was the primary cause of interrupted operations in the first year, including an outage exceeding 10 days.
doi:10.1007/s10278-010-9323-4
PMCID: PMC3033988  PMID: 20714916
Magnetic resonance imaging; computer networks; image distribution; wide area network (WAN); brain imaging; satellite-based networks; sub-Saharan Africa; DICOM router
3.  Assessment of Performance and Reliability of Computer-Aided Detection Scheme Using Content-Based Image Retrieval Approach and Limited Reference Database 
Journal of Digital Imaging  2010;24(2):352-359.
Content-based image retrieval approach was used in our computer-aided detection (CAD) schemes for breast cancer detection with mammography. In this study, we assessed CAD performance and reliability using a reference database including 1500 positive (breast mass) regions of interest (ROIs) and1500 normal ROIs. To test the relationship between CAD performance and the similarity level between the queried ROI and the retrieved ROIs, we applied a set of similarity thresholds to the retrieved similar ROIs selected by the CADschemes for all queried suspicious regions, and used only the ROIs that were above the threshold for assessing CAD performance at each threshold level. Using the leave-one-out testing method, we computed areas under receiver operating characteristic (ROC) curves (AZ) to assess CAD performance. The experimental results showed that as threshold increase, (1) less true positive ROIs can be referenced in the database than normal ROIs and (2) the AZ value was monotonically increased from 0.854±0.004 to 0.932±0.016. This study suggests that (1) in order to more accurately detect and diagnose subtle masses, a large and diverse database is required, and (2) assessing the reliability of the decision scores based on the similarity measurement is important in application of the CBIR-based CAD schemes when the limited database is used.
doi:10.1007/s10278-010-9281-x
PMCID: PMC2896988  PMID: 20204448
Content-based image retrieval; computer-aided diagnosis (CAD); cancer detection; computerized method
4.  Anatomically Anchored Template-Based Level Set Segmentation: Application to Quadriceps Muscles in MR Images from the Osteoarthritis Initiative 
In this paper, we present a semi-automated segmentation method for magnetic resonance images of the quadriceps muscles. Our method uses an anatomically anchored, template-based initialization of the level set-based segmentation approach. The method only requires the input of a single point from the user inside the rectus femoris. The templates are quantitatively selected from a set of images based on modes in the patient population, namely, sex and body type. For a given image to be segmented, a template is selected based on the smallest Kullback–Leibler divergence between the histograms of that image and the set of templates. The chosen template is then employed as an initialization for a level set segmentation, which captures individual anatomical variations in the image to be segmented. Images from 103 subjects were analyzed using the developed method. The algorithm was trained on a randomly selected subset of 50 subjects (25 men and 25 women) and tested on the remaining 53 subjects. The performance of the algorithm on the test set was compared against the ground truth using the Zijdenbos similarity index (ZSI). The average ZSI means and standard deviations against two different manual readers were as follows: rectus femoris, 0.78±0.12; vastus intermedius, 0.79±0.10; vastus lateralis, 0.82±0.08; and vastus medialis, 0.69±0.16.
doi:10.1007/s10278-009-9260-2
PMCID: PMC2891211  PMID: 20049623
Osteoarthritis; MRI; muscle segmentation; templates; level sets
5.  Anatomically Anchored Template-Based Level Set Segmentation: Application to Quadriceps Muscles in MR Images from the Osteoarthritis Initiative 
Journal of Digital Imaging  2010;24(1):28-43.
In this paper, we present a semi-automated segmentation method for magnetic resonance images of the quadriceps muscles. Our method uses an anatomically anchored, template-based initialization of the level set-based segmentation approach. The method only requires the input of a single point from the user inside the rectus femoris. The templates are quantitatively selected from a set of images based on modes in the patient population, namely, sex and body type. For a given image to be segmented, a template is selected based on the smallest Kullback–Leibler divergence between the histograms of that image and the set of templates. The chosen template is then employed as an initialization for a level set segmentation, which captures individual anatomical variations in the image to be segmented. Images from 103 subjects were analyzed using the developed method. The algorithm was trained on a randomly selected subset of 50 subjects (25 men and 25 women) and tested on the remaining 53 subjects. The performance of the algorithm on the test set was compared against the ground truth using the Zijdenbos similarity index (ZSI). The average ZSI means and standard deviations against two different manual readers were as follows: rectus femoris, 0.78 ± 0.12; vastus intermedius, 0.79 ± 0.10; vastus lateralis, 0.82 ± 0.08; and vastus medialis, 0.69 ± 0.16.
doi:10.1007/s10278-009-9260-2
PMCID: PMC2891211  PMID: 20049623
Osteoarthritis; MRI; muscle segmentation; templates; level sets
6.  Fusion of Color Doppler and Magnetic Resonance Images of the Heart 
Journal of Digital Imaging  2011;24(6):1024-1030.
This study was designed to establish and analyze color Doppler and magnetic resonance fusion images of the heart, an approach for simultaneous testing of cardiac pathological alterations, performance, and hemodynamics. Ten volunteers were tested in this study. The echocardiographic images were produced by Philips IE33 system and the magnetic resonance images were generated from Philips 3.0-T system. The fusion application was implemented on MATLAB platform utilizing image processing technology. The fusion image was generated from the following steps: (1) color Doppler blood flow segmentation, (2) image registration of color Doppler and magnetic resonance imaging, and (3) image fusion of different image types. The fusion images of color Doppler blood flow and magnetic resonance images were implemented by MATLAB programming in our laboratory. Images and videos were displayed and saved as AVI and JPG. The present study shows that the method we have developed can be used to fuse color flow Doppler and magnetic resonance images of the heart. We believe that the method has the potential to: fill in information missing from the ultrasound or MRI alone, show structures outside the field of view of the ultrasound through MR imaging, and obtain complementary information through the fusion of the two imaging methods (structure from MRI and function from ultrasound).
Electronic supplementary material
The online version of this article (doi:10.1007/s10278-011-9393-y) contains supplementary material, which is available to authorized users.
doi:10.1007/s10278-011-9393-y
PMCID: PMC3212677  PMID: 21656081
Biomedical image analysis; Image fusion; Digital image processing; Digital imaging and communications in medicine (DICOM); Cardiac imaging; MR imaging
7.  Fusion of Color Doppler and Magnetic Resonance Images of the Heart 
Journal of Digital Imaging  2011;24(6):1024-1030.
This study was designed to establish and analyze color Doppler and magnetic resonance fusion images of the heart, an approach for simultaneous testing of cardiac pathological alterations, performance, and hemodynamics. Ten volunteers were tested in this study. The echocardiographic images were produced by Philips IE33 system and the magnetic resonance images were generated from Philips 3.0-T system. The fusion application was implemented on MATLAB platform utilizing image processing technology. The fusion image was generated from the following steps: (1) color Doppler blood flow segmentation, (2) image registration of color Doppler and magnetic resonance imaging, and (3) image fusion of different image types. The fusion images of color Doppler blood flow and magnetic resonance images were implemented by MATLAB programming in our laboratory. Images and videos were displayed and saved as AVI and JPG. The present study shows that the method we have developed can be used to fuse color flow Doppler and magnetic resonance images of the heart. We believe that the method has the potential to: fill in information missing from the ultrasound or MRI alone, show structures outside the field of view of the ultrasound through MR imaging, and obtain complementary information through the fusion of the two imaging methods (structure from MRI and function from ultrasound).
Electronic supplementary material
The online version of this article (doi:10.1007/s10278-011-9393-y) contains supplementary material, which is available to authorized users.
doi:10.1007/s10278-011-9393-y
PMCID: PMC3212677  PMID: 21656081
Biomedical image analysis; Image fusion; Digital image processing; Digital imaging and communications in medicine (DICOM); Cardiac imaging; MR imaging
8.  Assessment of Performance and Reliability of Computer-Aided Detection Scheme Using Content-based Image Retrieval Approach and Limited Reference Database 
Content-based image retrieval approach was used in our computer-aided detection (CAD) schemes for breast cancer detection with mammography. In this study, we assessed CAD performance and reliability using a reference database including 1500 positive (breast mass) regions of interest (ROIs) and 1500 normal ROIs. To test the relationship between CAD performance and the similarity level between the queried ROI and the retrieved ROIs, we applied a set of similarity thresholds to the retrieved similar ROIs selected by the CAD schemes for all queried suspicious regions, and used only the ROIs that were above the threshold for assessing CAD performance at each threshold level. Using the leave-one-out testing method, we computed areas under receiver operating characteristic (ROC) curves (AZ) to assess CAD performance. The experimental results showed that as threshold increase, (1) less true positive ROIs can be referenced in the database than normal ROIs and (2) the AZ value was monotonically increased from 0.854±0.004 to 0.932±0.016. This study suggests that (1) in order to more accurately detect and diagnose subtle masses, a large and diverse database is required, and (2) assessing the reliability of the decision scores based on the similarity measurement is important in application of the CBIR-based CAD schemes when the limited database is used.
doi:10.1007/s10278-010-9281-x
PMCID: PMC2896988  PMID: 20204448
9.  A Situational Alignment Framework for PACS 
Journal of Digital Imaging  2011;24(6):979-992.
This paper reports the outcomes of a study on an integrated situational alignment framework for picture archiving and communication systems (PACS) labeled as PISA. Following the design research cycle, complementary validation methods and pilot cases were used to assess the proposed framework and its operationalized survey. In this paper, the authors outline (a) the process of the framework’ development, (b) the validation process with its underlying iterative steps, (c) the outcomes of pilot cases, and (d) improvement opportunities to refine and further validate the PISA framework. Results of this study support empirical application of the framework to hospital enterprises in order to gain insights into their PACS maturity and alignment. We argue that the framework can be applied as a valuable tool for assessments, monitoring and benchmarking purposes and strategic PACS planning.
doi:10.1007/s10278-011-9368-z
PMCID: PMC3212678  PMID: 21380574
PACS; Alignment; Maturity; Performance; Framework; Assessment; Hospital enterprise
10.  A Situational Alignment Framework for PACS 
Journal of Digital Imaging  2011;24(6):979-992.
This paper reports the outcomes of a study on an integrated situational alignment framework for picture archiving and communication systems (PACS) labeled as PISA. Following the design research cycle, complementary validation methods and pilot cases were used to assess the proposed framework and its operationalized survey. In this paper, the authors outline (a) the process of the framework’ development, (b) the validation process with its underlying iterative steps, (c) the outcomes of pilot cases, and (d) improvement opportunities to refine and further validate the PISA framework. Results of this study support empirical application of the framework to hospital enterprises in order to gain insights into their PACS maturity and alignment. We argue that the framework can be applied as a valuable tool for assessments, monitoring and benchmarking purposes and strategic PACS planning.
doi:10.1007/s10278-011-9368-z
PMCID: PMC3212678  PMID: 21380574
PACS; Alignment; Maturity; Performance; Framework; Assessment; Hospital enterprise
11.  A Web-Based Flexible Communication System in Radiology 
Journal of Digital Imaging  2010;24(5):890-896.
A web-based system for rapid multidirectional communication has been created in the Radiology department at San Francisco General Hospital. The system allows messaging among radiology attendings, residents, and technologists, as well as other members of the hospital community, such as Emergency Department physicians and nurses. Instead of being tied to a particular workflow, this system provides a flexible communication infrastructure which can be easily adapted for different functions and user roles. The system has so far been configured to successfully support the standard “wet reading” workflow, to support marking and tracking of critical results, as well as multiple educational and quality improvement workflows. In the 19 months of operation, the system has gained over 1,800 users (virtually all providers at our institution), it has been accessed by radiologists over 39,000 times and by non-radiologists over 34,000 times. It has become an integral part of the radiology department operations and non-radiology clinical workflows. Unlike most existing softwares, our system is not a task-specific application, but a multipurpose communication system. It is able to effectively accommodate multiple workflows and user roles through configuration (without additional programming). This flexibility has helped this system to be rapidly and widely adopted within our enterprise. The extended reach of the system enables improved monitoring and documentation of workflows, helping with management decision making, and quality assurance. We report a successful radiology communication system based on the principles of flexibility and inclusiveness of users inside and outside the radiology department.
doi:10.1007/s10278-010-9351-0
PMCID: PMC3180535  PMID: 21152949
Administration; Auditing; Clinical information systems; Clinical workflow; Communication; Computer communication networks; Computerized method; Critical results reporting; Efficiency; Electronic medical record (EMR); Workflow; Hospital information systems (HIS); Radiology workflow; Medical records system; Computerized; Quality assurance
12.  A Web-Based Flexible Communication System in Radiology 
Journal of Digital Imaging  2010;24(5):890-896.
A web-based system for rapid multidirectional communication has been created in the Radiology department at San Francisco General Hospital. The system allows messaging among radiology attendings, residents, and technologists, as well as other members of the hospital community, such as Emergency Department physicians and nurses. Instead of being tied to a particular workflow, this system provides a flexible communication infrastructure which can be easily adapted for different functions and user roles. The system has so far been configured to successfully support the standard “wet reading” workflow, to support marking and tracking of critical results, as well as multiple educational and quality improvement workflows. In the 19 months of operation, the system has gained over 1,800 users (virtually all providers at our institution), it has been accessed by radiologists over 39,000 times and by non-radiologists over 34,000 times. It has become an integral part of the radiology department operations and non-radiology clinical workflows. Unlike most existing softwares, our system is not a task-specific application, but a multipurpose communication system. It is able to effectively accommodate multiple workflows and user roles through configuration (without additional programming). This flexibility has helped this system to be rapidly and widely adopted within our enterprise. The extended reach of the system enables improved monitoring and documentation of workflows, helping with management decision making, and quality assurance. We report a successful radiology communication system based on the principles of flexibility and inclusiveness of users inside and outside the radiology department.
doi:10.1007/s10278-010-9351-0
PMCID: PMC3180535  PMID: 21152949
Administration; Auditing; Clinical information systems; Clinical workflow; Communication; Computer communication networks; Computerized method; Critical results reporting; Efficiency; Electronic medical record (EMR); Workflow; Hospital information systems (HIS); Radiology workflow; Medical records system; Computerized; Quality assurance
13.  Validation of Results from Knowledge Discovery: Mass Density as a Predictor of Breast Cancer 
The purpose of our study is to identify and quantify the association between high breast mass density and breast malignancy using inductive logic programming (ILP) and conditional probabilities, and validate this association in an independent dataset. We ran our ILP algorithm on 62,219 mammographic abnormalities. We set the Aleph ILP system to generate 10,000 rules per malignant finding with a recall >5% and precision >25%. Aleph reported the best rule for each malignant finding. A total of 80 unique rules were learned. A radiologist reviewed all rules and identified potentially interesting rules. High breast mass density appeared in 24% of the learned rules. We confirmed each interesting rule by calculating the probability of malignancy given each mammographic descriptor. High mass density was the fifth highest ranked predictor. To validate the association between mass density and malignancy in an independent dataset, we collected data from 180 consecutive breast biopsies performed between 2005 and 2007. We created a logistic model with benign or malignant outcome as the dependent variable while controlling for potentially confounding factors. We calculated odds ratios based on dichomotized variables. In our logistic regression model, the independent predictors high breast mass density (OR 6.6, CI 2.5–17.6), irregular mass shape (OR 10.0, CI 3.4–29.5), spiculated mass margin (OR 20.4, CI 1.9–222.8), and subject age (β=0.09, p<0.0001) significantly predicted malignancy. Both ILP and conditional probabilities show that high breast mass density is an important adjunct predictor of malignancy, and this association is confirmed in an independent data set of prospectively collected mammographic findings.
doi:10.1007/s10278-009-9235-3
PMCID: PMC2950275  PMID: 19760292
Data mining; mammography; machine learning
14.  Tarsal and Metatarsal Bone Mineral Density Measurement using Volumetric Quantitative Computed Tomography 
A new method for measuring bone mineral density (BMD) of the tarsal and metatarsals is described using volumetric quantitative computed tomography (VQCT) in subjects with diabetes mellitus and peripheral neuropathy. VQCT images of a single foot were acquired twice from eight subjects (mean age 51 [11 SD], seven male, one female). The cortical shells of the seven tarsal and five metatarsal bones were identified and semi-automatically segmented from adjacent bones. Volume and BMD of each bone were measured separately from the two acquired scans for each subject. Whole bone semi-automatic segmentation measurement errors were determined as the root mean square coefficient of variation for the volume and BMD of 0.8% and 0.9%, respectively. In addition to the whole-bone segmentation methods, we performed atlas-based partitioning of sub-regions within the second metatarsal for all subjects, from which the volumes and BMDs were obtained for each sub-region. The sub-region measurement BMD errors (root mean square coefficient of variation) within the shaft, proximal end and distal end were shown to vary by approximately 1% between the two scans of each subject. The new methods demonstrated large variations in BMDs between the 12 bones of the foot within a subject and between subjects, and between sub-regions within the second metatarsal. These methods can provide an important outcome measure for clinical research trials investigating the effects of interventions, aging or disease progression on bone loss or gain in individual foot bones.
doi:10.1007/s10278-008-9118-z
PMCID: PMC2745489  PMID: 18478296
QCT; Bone Mineral Density; Foot; Diabetes Mellitus; Peripheral Neuropathy
15.  Semi-Automated Phalanx Bone Segmentation Using the Expectation Maximization Algorithm 
Medical imaging technologies have allowed for in vivo exploration and evaluation of the human musculoskeletal system. Three-dimensional bone models generated using image segmentation techniques provide a means to optimize individualized orthopaedic surgical procedures using engineering analyses. However, many of the current segmentation techniques are not clinically practical due to the required time and human intervention. As a proof of concept, we demonstrate the use of an expectation maximization (EM) algorithm to segment the hand phalanx bones, and hypothesize that this semi-automated technique will improve on the efficiency while providing similar definitions as compared to a manual rater. Our results show a relative overlap of the proximal, middle, and distal phalanx bones of 0.83, 0.79, and 0.72 for the EM technique when compared to validated manual segmentations. The EM segmentations were also compared to 3D surface scans of the cadaveric specimens, which resulted in distance maps showing an average distance for the proximal, middle, and distal phalanx bones of 0.45, 0.46, and 0.51 mm, respectively. The EM segmentation improved on the segmentation speed of the manual techniques by a factor of eight. Overall, the manual segmentations had greater relative overlap metric values, which suggests that the manual segmentations are a better fit to the actual surface of the bone. As shown by the comparison to the bone surface scans, the EM technique provides a similar representation of the anatomic structure and offers an increase in efficiency that could help to reduce the time needed for defining anatomical structures from CT scans.
doi:10.1007/s10278-008-9151-y
PMCID: PMC2745490  PMID: 18769967
3D Segmentation; Bone and Bones; Hand; Computed Tomography; Artificial Neural Network
16.  Tarsal and Metatarsal Bone Mineral Density Measurement Using Volumetric Quantitative Computed Tomography 
A new method for measuring bone mineral density (BMD) of the tarsal and metatarsals is described using volumetric quantitative computed tomography (VQCT) in subjects with diabetes mellitus and peripheral neuropathy. VQCT images of a single foot were acquired twice from eight subjects (mean age 51 [11 SD], seven males, one female). The cortical shells of the seven tarsal and five metatarsal bones were identified and semiautomatically segmented from adjacent bones. Volume and BMD of each bone were measured separately from the two acquired scans for each subject. Whole-bone semiautomatic segmentation measurement errors were determined as the root mean square coefficient of variation for the volume and BMD of 0.8% and 0.9%, respectively. In addition to the whole-bone segmentation methods, we performed atlas-based partitioning of subregions within the second metatarsal for all subjects, from which the volumes and BMDs were obtained for each subregion. The subregion measurement BMD errors (root mean square coefficient of variation) within the shaft, proximal end, and distal end were shown to vary by approximately 1% between the two scans of each subject. The new methods demonstrated large variations in BMDs between the 12 bones of the foot within a subject and between subjects, and between subregions within the second metatarsal. These methods can provide an important outcome measure for clinical research trials investigating the effects of interventions, aging, or disease progression on bone loss, or gain, in individual foot bones.
doi:10.1007/s10278-008-9118-z
PMCID: PMC2745489  PMID: 18478296
QCT; bone mineral density; foot; diabetes mellitus; peripheral neuropathy
17.  Semi-automated Phalanx Bone Segmentation Using the Expectation Maximization Algorithm 
Medical imaging technologies have allowed for in vivo exploration and evaluation of the human musculoskeletal system. Three-dimensional bone models generated using image-segmentation techniques provide a means to optimize individualized orthopedic surgical procedures using engineering analyses. However, many of the current segmentation techniques are not clinically practical due to the required time and human intervention. As a proof of concept, we demonstrate the use of an expectation maximization (EM) algorithm to segment the hand phalanx bones, and hypothesize that this semi-automated technique will improve the efficiency while providing similar definitions as compared to a manual rater. Our results show a relative overlap of the proximal, middle, and distal phalanx bones of 0.83, 0.79, and 0.72 for the EM technique when compared to validated manual segmentations. The EM segmentations were also compared to 3D surface scans of the cadaveric specimens, which resulted in distance maps showing an average distance for the proximal, middle, and distal phalanx bones of 0.45, 0.46, and 0.51 mm, respectively. The EM segmentation improved on the segmentation speed of the manual techniques by a factor of eight. Overall, the manual segmentations had greater relative overlap metric values, which suggests that the manual segmentations are a better fit to the actual surface of the bone. As shown by the comparison to the bone surface scans, the EM technique provides a similar representation of the anatomic structure and offers an increase in efficiency that could help to reduce the time needed for defining anatomical structures from CT scans.
doi:10.1007/s10278-008-9151-y
PMCID: PMC2745490  PMID: 18769967
3D Segmentation; bone; hand; computed tomography; artificial neural network
18.  K-Bayes Reconstruction for Perfusion MRI II: Modeling and Technical Development 
Despite the continued spread of magnetic resonance imaging (MRI) methods in scientific studies and clinical diagnosis, MRI applications are mostly restricted to high-resolution modalities, such as structural MRI. While perfusion MRI gives complementary information on blood flow in the brain, its reduced resolution limits its power for detecting specific disease effects on perfusion patterns. This reduced resolution is compounded by artifacts such as partial volume effects, Gibbs ringing, and aliasing, which are caused by necessarily limited k-space sampling and the subsequent use of discrete Fourier transform (DFT) reconstruction. Here, a Bayesian modeling procedure (K-Bayes) is developed for the reconstruction of perfusion MRI. The K-Bayes approach combines a process model for the MRI signal in k-space with a Markov random field prior distribution that incorporates high-resolution segmented structural MRI information. A simulation study, described in Part I (Concepts and Applications), was performed to determine qualitative and quantitative improvements in K-Bayes reconstructed images compared with those obtained via DFT. The improvements were validated using in vivo perfusion MRI data of the human brain. The K-Bayes reconstructed images were demonstrated to provide reduced bias, increased precision, greater effect sizes, and higher resolution than those obtained using DFT.
doi:10.1007/s10278-009-9184-x
PMCID: PMC2896642  PMID: 19274427
Bayesian reconstruction; K-Bayes; Markov random field; Perfusion MRI; Structural MRI
19.  K-Bayes Reconstruction for Perfusion MRI I: Concepts and Application 
Despite the continued spread of magnetic resonance imaging (MRI) methods in scientific studies and clinical diagnosis, MRI applications are mostly restricted to high-resolution modalities, such as structural MRI. While perfusion MRI gives complementary information on blood flow in the brain, its reduced resolution limits its power for detecting specific disease effects on perfusion patterns. This reduced resolution is compounded by artifacts such as partial volume effects, Gibbs ringing, and aliasing, which are caused by necessarily limited k-space sampling and the subsequent use of discrete Fourier transform (DFT) reconstruction. In this study, a Bayesian modeling procedure (K-Bayes) is developed for the reconstruction of perfusion MRI. The K-Bayes approach (described in detail in Part II: Modeling and Technical Development) combines a process model for the MRI signal in k-space with a Markov random field prior distribution that incorporates high-resolution segmented structural MRI information. A simulation study was performed to determine qualitative and quantitative improvements in K-Bayes reconstructed images compared with those obtained via DFT. The improvements were validated using in vivo perfusion MRI data of the human brain. The K-Bayes reconstructed images were demonstrated to provide reduced bias, increased precision, greater effect sizes, and higher resolution than those obtained using DFT.
doi:10.1007/s10278-009-9183-y
PMCID: PMC2865632  PMID: 19205805
Bayesian reconstruction; K-Bayes; Markov random field; perfusion MRI; structural MRI
20.  Silent Cerebral Infarct Transfusion (SIT) Trial Imaging Core: Application of Novel Imaging Information Technology for Rapid and Central Review of MRI of the Brain 
The Silent Cerebral Infarct Multicenter Transfusion (SIT) Trial is a multi-institutional intervention trial in which children with silent cerebral infarcts are randomized to receive either blood transfusion therapy or observation (standard care) for 36 months. The SIT Trial is scheduled to enroll approximately 1,880 children with sickle cell disease from 29 clinical sites in the United States, Canada, UK, and France. Each child undergoes a screening magnetic resonance imaging (MRI) of the brain to detect the presence of silent cerebral infarct-like lesions, a pre-randomization (baseline) MRI and exit MRI to determine if there are new or enlarged cerebral infarcts, using a designated, prospective imaging protocol. The objective of this manuscript is to describe the innovative method used to process and adjudicate imaging studies for an international trial with a primary endpoint that includes neuroimaging. Institution investigators at each site were provided with computer hardware and software for transmission of MRI images that allow them to strip the scans of all personal information and add unique study identifiers. Three neuroradiologists at separate academic centers review MRI studies and determine the presence or absence of silent cerebral infarct-like lesions. Their findings are subsequently placed on web-based case report forms and sent to the Statistical Coordinating Center. The average time from imaging center receipt of the MRI study to the radiology committee report back to the local site is less than two working days. This novel strategy was designed to maximize efficiency and minimize cost of a complex large multicenter trial that depends heavily on neuroimaging for entry criteria and assessment for the primary outcome measures. The technology, process, and expertise used in the SIT Trial can be adapted to virtually any clinical research trial with digital imaging requirements.
doi:10.1007/s10278-008-9114-3
PMCID: PMC2801625  PMID: 18398653
Clinical trial imaging; PHI; case report forms; central review
21.  From the Editor's Desk 
Journal of Digital Imaging  2010;23(2):107-108.
doi:10.1007/s10278-010-9278-5
PMCID: PMC2837184  PMID: 20195694
23.  Free Stuff for Your Computer 
Journal of Digital Imaging  2010;23(2):238-239.
doi:10.1007/s10278-010-9280-y
PMCID: PMC2837192
25.  Uncovering and Improving Upon the Inherent Deficiencies of Radiology Reporting through Data Mining 
Journal of Digital Imaging  2010;23(2):109-118.
Uncertainty has been the perceived Achilles heel of the radiology report since the inception of the free-text report. As a measure of diagnostic confidence (or lack thereof), uncertainty in reporting has the potential to lead to diagnostic errors, delayed clinical decision making, increased cost of healthcare delivery, and adverse outcomes. Recent developments in data mining technologies, such as natural language processing (NLP), have provided the medical informatics community with an opportunity to quantify report concepts, such as uncertainty. The challenge ahead lies in taking the next step from quantification to understanding, which requires combining standardized report content, data mining, and artificial intelligence; thereby creating Knowledge Discovery Databases (KDD). The development of this database technology will expand our ability to record, track, and analyze report data, along with the potential to create data-driven and automated decision support technologies at the point of care. For the radiologist community, this could improve report content through an objective and thorough understanding of uncertainty, identifying its causative factors, and providing data-driven analysis for enhanced diagnosis and clinical outcomes.
doi:10.1007/s10278-010-9279-4
PMCID: PMC2837185  PMID: 20162438
Uncertainty; reporting; data mining

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