Radiology conferences enable participants the opportunity to ask experts questions through question and answer (Q and A) sessions or individually. Given the time limitations and intimidating circumstances, we incorporated conference text messaging (confexting) as a method of increasing interactivity between the audience and speakers. During a 5-day radiology conference, text messaging was utilized for anonymous interactivity between the audience and speakers during Q and A sessions. There were 324 text messages; 76 of these were either follow-up statements or questions related to earlier text messages. Forty-two questions were submitted via paper notes. There was a general trend of an increasing number of text messages and a decreasing number of paper notes. The anonymous text messaging system was found to be an effective method for interactivity between the audience and the speakers. The questions and answers could be presented in a PowerPoint format at the formal Q and A sessions. Questions texted to the authors during their talks could be immediately answered or addressed in subsequent talks. Although difficult for some individuals to embrace technology, confexting allows for interactivity and prompts discussion. Confexting is an effective method for interactivity between the audience and speakers not previously utilized in a conference setting. The anonymity and asynchronous communication enable conference participants to submit more questions than in the traditional setting. The speakers may be able to explain more thoroughly difficult concepts more thoroughly with additional slides at Q and A sessions or may immediately answer texted questions during their talks.
Teaching; Continuing medical education; Computer hardware; Communication; Education; Medical; Experiential; Imaging informatics; User interface
Successful adoption of new technology development can be accentuated by learning and applying the scientific principles of innovation diffusion. This is of particular importance to areas within the medical imaging practice which have lagged in innovation; perhaps, the most notable of which is reporting which has remained relatively stagnant for over a century. While the theoretical advantages of structured reporting have been well documented throughout the medical imaging community, adoption to date has been tepid and largely relegated to the academic and breast imaging communities. Widespread adoption will likely require an alternative approach to innovation, which addresses the heterogeneity and diversity of the practicing radiologist community along with the ever-changing expectations in service delivery. The challenges and strategies for reporting innovation and adoption are discussed, with the goal of adapting and customizing new technology to the preferences and needs of individual end-users.
Innovation adoption; Structured reporting; Medical imaging
In this paper, we present an effective method to determine the reference point of symphysis pubis (SP) in an axial stack of CT images to facilitate image registration for pelvic cancer treatment. In order to reduce the computational time, the proposed method consists of two detection parts, the coarse detector, and the fine detector. The detectors check each image patch whether it contains the characteristic structure of SP. The coarse detector roughly determines the location of the reference point of SP using three types of information, which are the location and intensity of an image patch, the SP appearance, and the geometrical structure of SP. The fine detector examines around the location found by the coarse detection to refine the location of the reference point of SP. In the experiment, the average location error of the propose method was 2.23 mm, which was about the side length of two pixels. Considering that the average location error by a radiologist is 0.77 mm, the proposed method finds the reference point quite accurately. Since it takes about 10 s to locate the reference point from a stack of CT images, it is fast enough to use in real time to facilitate image registration of CT images for pelvic cancer treatment.
Computer-aided diagnosis (CAD); Image registration; Pattern recognition; Computed tomography; Symphysis pubis; Haar-like features; Biased discriminant analysis
We have developed a method to quantify the shape of liver lesions in CT images and to evaluate its performance for retrieval of images with similarly-shaped lesions. We employed a machine learning method to combine several shape descriptors and defined similarity measures for a pair of shapes as a weighted combination of distances calculated based on each feature. We created a dataset of 144 simulated shapes and established several reference standards for similarity and computed the optimal weights so that the retrieval result agrees best with the reference standard. Then we evaluated our method on a clinical database consisting of 79 portal-venous-phase CT liver images, where we derived a reference standard of similarity from radiologists’ visual evaluation. Normalized Discounted Cumulative Gain (NDCG) was calculated to compare this ordering with the expected ordering based on the reference standard. For the simulated lesions, the mean NDCG values ranged from 91% to 100%, indicating that our methods for combining features were very accurate in representing true similarity. For the clinical images, the mean NDCG values were still around 90%, suggesting a strong correlation between the computed similarity and the independent similarity reference derived the radiologists.
Image retrieval; Image analysis; Image processing
The aims of this study were to (1) investigate the repeatability of measured volumes using the atlas-based method in each area of the brain, and (2) validate our hypothesis that the repeatability of the measured volumes with the atlas-based method was improved by using smoothed images. T1-weighted magnetic resonance images were obtained in five healthy subjects using the 1.5-T scanner. We used Statistical Parametric Mapping 5 and WFU PickAtlas software (theory of the Talairach brain atlas). Volumes inside region-of-interest (ROI) were measured in ten sets (five subjects × right and left) on six ROIs, respectively. One set comprises five images (one subject × five 3D-T1WIs). The percentage change was defined as [100 × (measured volume–mean volume in each set)/mean volume in each set)]. As a result, the average percentage changes using non-smoothed image on each ROI were as follows: gray matter, 0.482%; white matter, 0.375%; cerebrospinal fluid images, 0.731%; hippocampus, 0.864%; orbital gyrus, 1.692%; cerebellum posterior lobe, 0.854%. Using smoothed images with large FWHM resulted in improved repeatability on orbital gyrus. This is the first report of repeatability in each brain structure and improved repeatability with smoothed images using the atlas-based method.
Atlas-based method; Brain volumetry; Magnetic resonance imaging; Repeatability; WFU PickAtlas; Brain imaging; Brain mapping; Brain morphology; Clinical application; Computer analysis; Image analysis
Image processing turns out to be essential in the planning and verification of radiotherapy treatments. Before applying a radiotherapy treatment, a dosimetry planning must be performed. Usually, the planning is done by means of an X-ray volumetric analysis using computerized tomography, where the area to be radiated is marked out. During the treatment phase, it is necessary to place the patient under the particle accelerator exactly as considered in the dosimetry stage. Coarse alignment is achieved using fiduciary markers placed over the patient’s skin as external references. Later, fine alignment is provided by comparing a digitally reconstructed radiography (DRR) from the planning stage and a portal image captured by the accelerator in the treatment stage. The preprocessing of DRR and portal images, as well as the minimization of the non-shared information between both kinds of images, is mandatory for the correct operation of the image registration algorithm. With this purpose, mathematical morphology and image processing techniques have been used. The present work describes a fully automatic method to calculate more accurately the necessary displacement of the couch to place the patient exactly at the planned position. The proposed method to achieve the correct positioning of the patient is based on advanced image registration techniques. Preliminary results show a perfect match with the displacement estimated by the physician.
Radiotherapy; Image registration; Image feature enhancement; Biomedical image analysis
This paper presents a novel method which reconstructs any desired 3D image resolution from raw cone-beam CT data. X-ray attenuation through the object is approximated using ridgelet basis functions which allow us to have multiresolution representation levels. Since the Radon data have preferential orientations by nature, a spherical wavelet transform is used to compute the ridgelet coefficients from the Radon shell data. The whole method uses the classical Grangeat’s relation for computing derivatives of the Radon data which are then integrated and projected to a spherical wavelet representation and back-reconstructed using a modified version of the well known back-projection algorithm. Unlike previous reconstruction methods, this proposal uses a multiscale representation of the Radon data and therefore allows fast display of low-resolution data level.
Computed tomography; 3D ridgelet; Spherical wavelets
The current array of PACS products and 3D visualization tools presents a wide range of options for applying advanced visualization methods in clinical radiology. The emergence of server-based rendering techniques creates new opportunities for raising the level of clinical image review. However, best-of-breed implementations of core PACS technology, volumetric image navigation, and application-specific 3D packages will, in general, be supplied by different vendors. Integration issues should be carefully considered before deploying such systems. This work presents a classification scheme describing five tiers of PACS modularity and integration with advanced visualization tools, with the goals of characterizing current options for such integration, providing an approach for evaluating such systems, and discussing possible future architectures. These five levels of increasing PACS modularity begin with what was until recently the dominant model for integrating advanced visualization into the clinical radiologist's workflow, consisting of a dedicated stand-alone post-processing workstation in the reading room. Introduction of context-sharing, thin clients using server-based rendering, archive integration, and user-level application hosting at successive levels of the hierarchy lead to a modularized imaging architecture, which promotes user interface integration, resource efficiency, system performance, supportability, and flexibility. These technical factors and system metrics are discussed in the context of the proposed five-level classification scheme.
PACS; 3D imaging (imaging, three-dimensional); Computer systems; Advanced visualization; Server-based rendering; Application hosting
Browser with Rich Internet Application (RIA) Web pages could be a powerful user interface for handling sophisticated data and applications. Then the RIA solutions would be a potential method for viewing and manipulating the most data generated in clinical processes, which can accomplish the main functionalities as general picture archiving and communication system (PACS) viewing systems. The aim of this study is to apply the RIA technology to present medical images. Both Digital Imaging and Communications in Medicine (DICOM) and non-DICOM data can be handled by our RIA solutions. Some clinical data that are especially difficult to present using PACS viewing systems, such as ECG waveform, pathology virtual slide microscopic image, and radiotherapy plan, are as well demonstrated. Consequently, clinicians can use browser as a unique interface for acquiring all the clinical data located in different departments and information systems. And the data could be presented appropriately and processed freely by adopting the RIA technologies.
Electronic supplementary material
The online version of this article (doi:10.1007/s10278-011-9374-1) contains supplementary material, which is available to authorized users.
PACS; Clinical application; Clinical image viewing; DICOM; XML; RIA
The evaluation of the carotid artery wall is essential for the diagnosis of cardiovascular pathologies or for the assessment of a patient’s cardiovascular risk. This paper presents a completely user-independent algorithm, which automatically extracts the far double line (lumen–intima and media–adventitia) in the carotid artery using an Edge Flow technique based on directional probability maps using the attributes of intensity and texture. Specifically, the algorithm traces the boundaries between the lumen and intima layer (line one) and between the media and adventitia layer (line two). The Carotid Automated Ultrasound Double Line Extraction System based on Edge-Flow (CAUDLES-EF) is characterized and validated by comparing the output of the algorithm with the manual tracing boundaries carried out by three experts. We also benchmark our new technique with the two other completely automatic techniques (CALEXia and CULEXsa) we previously published. Our multi-institutional database consisted of 300 longitudinal B-mode carotid images with normal and pathologic arteries. We compared our current new method with previous methods, and showed the mean and standard deviation for the three methods: CALEXia, CULEXsa, and CAUDLES-EF as 0.134 ± 0.088, 0.074 ± 0.092, and 0.043 ± 0.097 mm, respectively. Our IMT was slightly underestimated with respect to the ground truth IMT, but showed a uniform behavior over the entire database. Regarding the Figure of Merit (FoM), CALEXia and CULEXsa showed the values of 84.7% and 91.5%, respectively, while our new approach, CAUDLES-EF, performed the best at 94.8%, showing a good improvement compared to previous methods.
Carotid artery; Ultrasound; Multiresolution; Edge flow; Localization; Intima–media thickness; Hausdorff distance; Polyline distance; Segmentation; Automated measurement; Carotid imaging; Intima-media thickness measurement; Edge-flow operator
Aortoiliac and lower extremity arterial atherosclerotic plaque burden is a risk factor for the development of visceral and peripheral ischemic and aneurismal vascular disease. While prior research allows automated quantification of calcified plaque in these body regions using CT angiograms, no automated method exists to quantify soft plaque. We developed an automatic algorithm that defines the outer wall contour and wall thickness of vessels to quantify non-calcified plaque in CT angiograms of the chest, abdomen, pelvis, and lower extremities. The algorithm encodes the search space as a constrained graph and calculates the outer wall contour by deriving a minimum cost path through the graph, following the visible outer wall contour while minimizing path tortuosity. Our algorithm was statistically equivalent to a reference standard made by two reviewers. Absolute error was 1.9 ± 2.3% compared to the inter-observer variability of 3.9 ± 3.6%. Wall thickness in vessels with atherosclerosis was 3.4 ± 1.6 mm compared to 1.2 ± 0.4 mm in normal vessels. The algorithm shows promise as a tool for quantification of non-calcified plaque in CT angiography. When combined with previous research, our method has the potential to quantify both non-calcified and calcified plaque in all clinically significant systemic arteries, from the thoracic aorta to the arteries of the calf, over a wide range of diameters. This algorithm has the potential to enable risk stratification of patients and facilitate investigations into the relationships between asymptomatic atherosclerosis and a variety of behavioral, physiologic, pathologic, and genotypic conditions.
Soft plaque; Quantification; Algorithm; CT angiography; Arteries; Graph method
Glomerular filtration rate (GFR) is a common accepted standard estimation of renal function. Gamma camera-based methods for estimating renal uptake of 99mTc-diethylenetriaminepentaacetic acid (DTPA) without blood or urine sampling have been widely used. Of these, the method introduced by Gates has been the most common method. Currently, most of gamma cameras are equipped with a commercial program for GFR determination, a semi-quantitative analysis by manually drawing region of interest (ROI) over each kidney. Then, the GFR value can be computed from the scintigraphic determination of 99mTc-DTPA uptake within the kidney automatically. Delineating the kidney area is difficult when applying a fixed threshold value. Moreover, hand-drawn ROIs are tedious, time consuming, and dependent highly on operator skill. Thus, we developed a fully automatic renal ROI estimation system based on the temporal changes in intensity counts, intensity-pair distribution image contrast enhancement method, adaptive thresholding, and morphological operations that can locate the kidney area and obtain the GFR value from a 99mTc-DTPA renogram. To evaluate the performance of the proposed approach, 30 clinical dynamic renograms were introduced. The fully automatic approach failed in one patient with very poor renal function. Four patients had a unilateral kidney, and the others had bilateral kidneys. The automatic contours from the remaining 54 kidneys were compared with the contours of manual drawing. The 54 kidneys were included for area error and boundary error analyses. There was high correlation between two physicians’ manual contours and the contours obtained by our approach. For area error analysis, the mean true positive area overlap is 91%, the mean false negative is 13.4%, and the mean false positive is 9.3%. The boundary error is 1.6 pixels. The GFR calculated using this automatic computer-aided approach is reproducible and may be applied to help nuclear medicine physicians in clinical practice.
Glomerular filtration rate; Diethylenetriaminepentaacetic acid; Image contrast enhancement; Adaptive thresholding; Morphology operation; Renogram
One of the new challenges of Information Technology in the medical world is the protection and authentication of a variety of digital medical files, datasets, and images. In this work, the ability of magnetic resonance imaging (MRI) slice sequences to hide digital data is investigated and more specifically the case that the hidden data are the regions of interest (ROI) of the MRI slices. The regions of non-interest (RONI) are used as cover. The hiding capacity of the whole sequence is taken into account. Any ROI-targeted tampering attempt can be detected, and the original image can be self-restored (under certain conditions) by extracting the ROI from the RONI.
Medical imaging; MRI; ROI; Authentication; Self-correction; Integrity; JPEG2000
The pioneering work performed in the social sciences on diffusion of innovation can be applied to medical imaging and shed valuable insights as to how innovation is analyzed and adopted within the population of end-users. Successful innovation must take into account unique stakeholder differences, changes in communication and social interactions, and shifting priorities in market economics. The dramatic changes currently underway in current medical imaging practice provides unique innovation opportunities to those individuals and companies which can utilize this knowledge and effect change in objective and reproducible means. Successful innovation should rely upon data-driven objective analysis, which can scientifically validate the inherent strengths and weaknesses of the innovation, when compared with the idea or technology it supercedes.
Innovation; Technology development; Data mining
Numerous articles have offered instructions for working with advanced radiology images in Microsoft PowerPoint (Redmond, WA); however, no articles have detailed instructions to do the same on alternative presentation software. Apple Macintosh (Cupertino, CA) computers are gaining popularity with many radiologists, due in part to the availability of a powerful, free, open-source Digital Imaging and Communications in Medicine (DICOM) viewing and manipulating software OsiriX (http://www.osirix-viewer.com). Apple’s own presentation software, Keynote, is particularly effective in dealing with medical images and cine clips. This article demonstrates how to use Apple’s Keynote software to present radiology images and scrollable image stacks, without third-party add-on software. The article also illustrates how to compress media files and protect patient information in Keynote presentations. Lastly, it addresses the steps to converting between PowerPoint and Keynote file formats. Apple’s Keynote software enables quick and efficient addition of multiple static images or scrollable image stacks, compression of media files, and removal of patient information. These functions can be accomplished by inexperienced users with no software modifications.
Computers in medicine; Radiology Information Systems (RIS); Radiology teaching file; Image processing; Image display; Productivity; Keynote
Sacroiliac (SI) joint dislocations and sacral fractures of the pelvis can be stabilized by SI screws; however, screw insertion into a sacral isthmus region is risky for the adjacent neurovascular structures. Therefore, shape analyses of general SI screw corridors or safety zones are of great surgical interest; however, before such analyses can be conducted, a method for computing 3D models of general SI corridors from routine clinical computed tomography (CT) scans has to be developed. This work describes a method for determining general corridors in pelvic CT data for accurate screw placement into the first sacral body. The method is implemented with the computer language C++. The pelvic CT data are preprocessed before the presented algorithm computes a model of the 3D corridor volume. Additionally, the two most important parameters of the algorithm, the raster step and the virtual SI screw diameter, have been characterized. The result of the work is an algorithm for computing general SI screw corridors and its implementation. Additionally the influences of two important parameters, the raster step and the SI screw diameter, on corridor volume precision and computation time have been quantified for the test sample. We conclude that the method can be used in further corridor shape analyses with a large number of pelvic CT data sets for investigating general SI screw corridors and clinical consequences for the placements of the screws. Implementation of the presented software algorithm could also enhance performance of computer-assisted surgery in the near future.
3D imaging; image analysis; bone and bones; computed tomography; image processing; software design; pelvis
This software tool locates and computes the intensity of radiation skin dose resulting from fluoroscopically guided interventional procedures. It is comprised of multiple modules. Using standardized body specific geometric values, a software module defines a set of male and female patients arbitarily positioned on a fluoroscopy table. Simulated X-ray angiographic (XA) equipment includes XRII and digital detectors with or without bi-plane configurations and left and right facing tables. Skin dose estimates are localized by computing the exposure to each 0.01 × 0.01 m2 on the surface of a patient irradiated by the X-ray beam. Digital Imaging and Communications in Medicine (DICOM) Structured Report Dose data sent to a modular dosimetry database automatically extracts the 11 XA tags necessary for peak skin dose computation. Skin dose calculation software uses these tags (gantry angles, air kerma at the patient entrance reference point, etc.) and applies appropriate corrections of exposure and beam location based on each irradiation event (fluoroscopy and acquistions). A physicist screen records the initial validation of the accuracy, patient and equipment geometry, DICOM compliance, exposure output calibration, backscatter factor, and table and pad attenuation once per system. A technologist screen specifies patient positioning, patient height and weight, and physician user. Peak skin dose is computed and localized; additionally, fluoroscopy duration and kerma area product values are electronically recorded and sent to the XA database. This approach fully addresses current limitations in meeting accreditation criteria, eliminates the need for paper logs at a XA console, and provides a method where automated ALARA montoring is possible including email and pager alerts.
Peak skin dose; sentinal event; DICOM structured report dose; patient entrance reference point; fluoroscopy; interventional radiology; Joint Commission (JC); radiation dose; Digital Imaging and Communications in Medicine (DICOM)
Teleradiology applications and universal availability of patient records using web-based technology are rapidly gaining importance. Consequently, digital medical image security has become an important issue when images and their pertinent patient information are transmitted across public networks, such as the Internet. Health mandates such as the Health Insurance Portability and Accountability Act require healthcare providers to adhere to security measures in order to protect sensitive patient information. This paper presents a fully reversible, dual-layer watermarking scheme with tamper detection capability for medical images. The scheme utilizes concepts of public-key cryptography and reversible data-hiding technique. The scheme was tested using medical images in DICOM format. The results show that the scheme is able to ensure image authenticity and integrity, and to locate tampered regions in the images.
Digital watermark; security; image authentication; teleradiology; public-key cryptography
Pixel accuracy in images from high-resolution computed tomography (HRCT) is ultimately limited by reconstruction error and noise. While for visual analysis this may not be relevant, for computer-aided quantitative analysis in either densitometric, or shape studies aiming at accurate results, the impact of pixel uncertainty must be taken into consideration. In this work, we study several denoising methods: geometric mean filter, Wiener filtering, and wavelet denoising. The performance of each method was assessed through visual inspection, profile region intensity analysis, and global figures of merit, using images from brain and thoracic phantoms, as well as several real thoracic HRCT images.
Denoising methods; tomographic reconstruction; Poisson noise; computed tomography
This paper presents an automatic computer-aided detection scheme on digital chest radiographs to detect pneumoconiosis. Firstly, the lung fields are segmented from a digital chest X-ray image by using the active shape model method. Then, the lung fields are subdivided into six non-overlapping regions, according to Chinese diagnosis criteria of pneumoconiosis. The multi-scale difference filter bank is applied to the chest image to enhance the details of the small opacities, and the texture features are calculated from each region of the original and the processed images, respectively. After extracting the most relevant ones from the feature sets, support vector machine classifiers are utilized to separate the samples into the normal and the abnormal sets. Finally, the final classification is performed by the chest-based report-out and the classification probability values of six regions. Experiments are conducted on randomly selected images from our chest database. Both the training and the testing sets have 300 normal and 125 pneumoconiosis cases. In the training phase, training models and weighting factors for each region are derived. We evaluate the scheme using the full feature vectors or the selected feature vectors of the testing set. The results show that the classification performances are high. Compared with the previous methods, our fully automated scheme has a higher accuracy and a more convenient interaction. The scheme is very helpful to mass screening of pneumoconiosis in clinic.
Pneumoconiosis; digital radiography; computer-aided detection (CAD); active shape model (ASM); texture analysis; support vector machine (SVM)
The purpose of this work was to develop a visualization method for concurrent observation of both velocity and magnitude data obtained from through-plane velocity measurements using phase-contrast magnetic resonance imaging. Magnitude and velocity images were combined using an opacity transfer function (OTF) where the opacity was a function of a velocity range defined by the velocity encoding (venc) parameter. Measured velocities were color-coded according to a predefined color scale and then combined into one image with the gray-scale magnitude image according to the OTF. In the combined images, simultaneous information of velocity and anatomy was presented. The proposed visualization method facilitated the understanding of how the measured blood flow was related to the underlying anatomy. Results are shown where the method is used to visualize blood flow measurements in the ascending aorta and the aortic valve. Adjustments of the OTF render possible identification of the peak velocities and their localization. Forward and backward blood flow is easily shown when applying appropriate OTF and color-coding. An advantage when using the proposed method is the ability of developing standardized protocol settings since the velocity information is quantitative and not relative as is the case for data obtained from the magnitude images. The intended application of the visualization method is the analysis of common flow studies used in the diagnosis of different cardiovascular diseases.
Magnetic resonance imaging; image visualization; digital image management; MR imaging; user interface
Decision support systems have been used to promote the practice of evidence-based medicine. Computer-assisted diagnosis can serve as one element of evidence-based radiology. One area where such tools may provide benefit is analysis of vertebral compression fractures (VCFs), which can be a challenge in MRI interpretation. VCFs may be benign or malignant in etiology, and several MRI features may help to make this important distinction. We describe a web-based decision support system for discriminating benign from malignant VCFs as a prototype for a more general diagnostic decision support framework for radiologists. The system has three components: a feature checklist with an image gallery derived from proven reference cases, a prediction model, and a reporting mechanism. The website allows users to input the findings for a case to be interpreted using a structured feature checklist. The image gallery complements the checklist, for clarity and training purposes. The input from the checklist is then used to calculate the likelihood of malignancy by a logistic regression prediction model. Standardized report text is generated that summarizes pertinent positive and negative findings. This computer-assisted diagnosis system demonstrates the integration of three areas where diagnostic decision support can aid radiologists: first, in image interpretation, through feature checklists and illustrative image galleries; second, in feature-based prediction modeling; and third, in structured reporting. We present a diagnostic decision support tool that provides radiologists with evidence-based guidance for discriminating benign from malignant VCF. This model may be useful in other difficult-diagnosis situations and requires further clinical testing.
Decision support; computer-assisted diagnosis; compression fracture; magnetic resonance imaging; structured reporting
Color blending is a popular display method for functional and anatomic image fusion. The underlay image is typically displayed in grayscale, and the overlay image is displayed in pseudo colors. This pixel-level fusion provides too much information for reviewers to analyze quickly and effectively and clutters the display. To improve the fusion image reviewing speed and reduce the information clutter, a pixel-feature hybrid fusion method is proposed and tested for PET/CT images. Segments of the colormap are selectively masked to have a few discrete colors, and pixels displayed in the masked colors are made transparent. The colormap thus creates a false contouring effect on overlay images and allows the underlay to show through to give contours an anatomic context. The PET standardized uptake value (SUV) is used to control where colormap segments are masked. Examples show that SUV features can be extracted and blended with CT image instantaneously for viewing and diagnosis, and the non-feature part of the PET image is transparent. The proposed pixel-feature hybrid fusion highlights PET SUV features on CT images and reduces display clutters. It is easy to implement and can be used as complementarily to existing pixel-level fusion methods.
Image fusion; pixel-level fusion; feature-level fusion; pixel-feature hybrid fusion
To address potential concern for cumulative radiation exposure with serial spiral chest computed tomography (CT) scans in children with chronic lung disease, we developed an approach to match bronchial airways on low-dose spiral and low-dose high-resolution CT (HRCT) chest images to allow serial comparisons. An automated algorithm matches the position and orientation of bronchial airways obtained from HRCT slices with those in the spiral CT scan. To validate this algorithm, we compared manual matching vs automatic matching of bronchial airways in three pediatric patients. The mean absolute percentage difference between the manually matched spiral CT airway and the index HRCT airways were 9.4 ± 8.5% for the internal diameter measurements, 6.0 ± 4.1% for the outer diameter measurements, and 10.1 ± 9.3% for the wall thickness measurements. The mean absolute percentage difference between the automatically matched spiral CT airway measurements and index HRCT airway measurements were 9.2 ± 8.6% for the inner diameter, 5.8 ± 4.5% for the outer diameter, and 9.9 ± 9.5% for the wall thickness. The overall difference between manual and automated methods was 2.1 ± 1.2%, which was significantly less than the interuser variability of 5.1 ± 4.6% (p < 0.05). Tests of equivalence had p < 0.05, demonstrating no significant difference between the two methods. The time required for matching was significantly reduced in the automated method (p < 0.01) and was as accurate as manual matching, allowing efficient comparison of airways obtained on low-dose spiral CT imaging with low-dose HRCT scans.
Electronic supplementary material
The online version of this article (doi:10.1007/s10278-009-9199-3) contains supplementary material, which is available to authorized users.
3D imaging (imaging; three-dimensional); algorithms; chest CT; computer analysis; image analysis; image processing; image registration; imaging; three-dimensional; lung diseases; lung; radiation dose; reproducibility of results
This study evaluates the accuracy of augmenting initial intraprocedural computed tomography (CT) during radiofrequency ablation (RFA) of hepatic metastases with preprocedural positron emission tomography (PET) through a hardware-accelerated implementation of an automatic nonrigid PET–CT registration algorithm. The feasibility of augmenting intraprocedural CT with preprocedural PET to improve localization of CT-invisible but PET-positive tumors with images from actual RFA was explored. Preprocedural PET and intraprocedural CT images from 18 cases of hepatic RFA were included. All PET images in the study originated from a hybrid PET/CT scanner, and PET–CT registration was performed in two ways: (1) direct registration of preprocedural PET with intraprocedural CT and (2) indirect registration of preprocedural CT (i.e., the CT of hybrid PET/CT scan) with intraprocedural CT. A hardware-accelerated registration took approximately 2 min. Calculated registration errors were 7.0 and 8.4 mm for the direct and indirect methods, respectively. Overall, the direct registration was found to be statistically not distinct from that performed by a group of clinical experts. The accuracy, execution speed, and compactness of our implementation of nonrigid image registration suggest that existing PET can be overlaid on intraprocedural CT, promising a novel, technically feasible, and clinically viable approach for PET augmentation of CT guidance of RFA.
CT; Radiofrequency ablation; Image registration; Mutual information; PET