We created our imaging center (IC) to move outpatient imaging from our busy inpatient imaging suite off-site to a location that is more inviting to ambulatory patients. Nevertheless, patients scanned at our IC still represent the depth and breadth of illness complexity seen with our tertiary care population. Thus, we protocol exams on an individualized basis to ensure that the referring clinician’s question is fully answered by the exam performed. Previously, paper based protocoling was a laborious process for all those involved where the IC business office would fax the requests to various reading rooms for protocoling by the subspecialist radiologists who are 3 miles away at the main hospital. Once protocoled, reading room coordinators would fax back the protocoled request to the IC technical area in preparation for the next day’s scheduled exams. At any breakdown in this process (e.g., lost paperwork), patient exams were delayed and clinicians and patients became upset. To improve this process, we developed a paper free process whereby protocoling is accomplished through scanning of exam requests into our PACS. Using the common worklist functionality found in most PACS, we created “protocoling worklists” that contain these scanned documents. Radiologists protocol these studies in the PACS worklist (with the added benefit of having all imaging and report data available), and subsequently, the technologists can see and act on the protocols they find in PACS. This process has significantly decreased interruptions in our busy reading rooms and decreased rework of IC staff.
Radiology workflow; workflow re-engineering; PACS
Digital radiology departments could benefit from the ability to integrate and visualize data (e.g. information reflecting complex workflow states) from all of their imaging and information management systems in one composite presentation view. Leveraging data warehousing tools developed in the business world may be one way to achieve this capability. In total, the concept of managing the information available in this data repository is known as Business Intelligence or BI. This paper describes the concepts used in Business Intelligence, their importance to modern Radiology, and the steps used in the creation of a prototype model of a data warehouse for BI using open-source tools.
Data collection; data mining; databases; data extraction; knowledge management; online analytical processing (OLAP)
A temporal subtraction image, which is obtained by subtraction of a previous image from a current one, can be used for enhancing interval changes (such as formation of new lesions and changes in existing abnormalities) on medical images by removing most of the normal structures. However, subtraction artifacts are commonly included in temporal subtraction images obtained from thoracic computed tomography and thus tend to reduce its effectiveness in the detection of pulmonary nodules. In this study, we developed a new method for substantially removing the artifacts on temporal subtraction images of lungs obtained from multiple-detector computed tomography (MDCT) by using a voxel-matching technique. Our new method was examined on 20 clinical cases with MDCT images. With this technique, the voxel value in a warped (or nonwarped) previous image is replaced by a voxel value within a kernel, such as a small cube centered at a given location, which would be closest (identical or nearly equal) to the voxel value in the corresponding location in the current image. With the voxel-matching technique, the correspondence not only between the structures but also between the voxel values in the current and the previous images is determined. To evaluate the usefulness of the voxel-matching technique for removal of subtraction artifacts, the magnitude of artifacts remaining in the temporal subtraction images was examined by use of the full width at half maximum and the sum of a histogram of voxel values, which may indicate the average contrast and the total amount, respectively, of subtraction artifacts. With our new method, subtraction artifacts due to normal structures such as blood vessels were substantially removed on temporal subtraction images. This computerized method can enhance lung nodules on chest MDCT images without disturbing misregistration artifacts.
Temporal subtraction; nonlinear warping; computer-aided diagnosis; chest CT; image registration
In this paper, we compare five common classifier families in their ability to categorize six lung tissue patterns in high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD) and with healthy tissue. The evaluated classifiers are naive Bayes, k-nearest neighbor, J48 decision trees, multilayer perceptron, and support vector machines (SVM). The dataset used contains 843 regions of interest (ROI) of healthy and five pathologic lung tissue patterns identified by two radiologists at the University Hospitals of Geneva. Correlation of the feature space composed of 39 texture attributes is studied. A grid search for optimal parameters is carried out for each classifier family. Two complementary metrics are used to characterize the performances of classification. These are based on McNemar’s statistical tests and global accuracy. SVM reached best values for each metric and allowed a mean correct prediction rate of 88.3% with high class-specific precision on testing sets of 423 ROIs.
Quantitative image analysis; feature extraction; texture analysis; chest high-resolution CT; supervised learning; support vector machines
Bronchoscopy is often performed for staging lung cancer. The recent development of multidetector computed tomography (MDCT) scanners and ultrathin bronchoscopes now enable the bronchoscopic biopsy and treatment of peripheral diagnostic regions of interest (ROIs). Because these ROIs are often located several generations within the airway tree, careful planning and interpretation of the bronchoscopic route is required prior to a procedure. The current practice for planning bronchoscopic procedures, however, is difficult, error prone, and time consuming. To alleviate these issues, we propose a method for producing and previewing reports for bronchoscopic procedures using patient-specific MDCT chest scans. The reports provide quantitative data about the bronchoscopic routes and both static and dynamic previews of the proper airway route. The previews consist of virtual bronchoscopic endoluminal renderings along the route and three-dimensional cues for a final biopsy site. The reports require little storage space and computational resources, enabling physicians to view the reports on a portable tablet PC. To evaluate the efficacy of the reporting system, we have generated reports for 22 patients in a human lung cancer patient pilot study. For 17 of these patients, we used the reports in conjunction with live image-based bronchoscopic guidance to direct physicians to central chest and peripheral ROIs for subsequent diagnostic evaluation. Our experience shows that the tool enabled useful procedure preview and an effective means for planning strategy prior to a live bronchoscopy.
Image-based reporting; image-guided surgery; 3D imaging; virtual bronchoscopy; lung cancer; bronchoscopy
Picture archiving and communication systems (PACS) for imaging studies is rapidly being adopted in hospitals throughout the UK. However, very little comparison has been made between PACS and laser hard copies for assessing the diagnostic accuracy of detecting fractures by emergency physicians. A prospective paired comparison study was undertaken looking at correct reporting of scaphoid X-rays on PACS and conventional film by emergency department medical staff. A total of 34 imaging studies were reported by 38 physicians using both PACS workstations and laser-printed films. The percentage of emergency physicians correctly reporting imaging studies was similar when comparing PACS images to laser film copies (80.7% versus 81.0%). The sensitivity and specificity of PACS for diagnosing scaphoid fractures was 79.5% and 81.6%, versus 78.1% and 83.8% for conventional films. There is no significant difference in accuracy of diagnosis between PACS and laser film copies when scaphoid X-rays are reported by emergency physicians.
PACS; PACS system performance; performance measurement
The purpose of this study was to study whether the benefits from introducing a picture archiving and communication systems (PACS) reported by innovators and early adopters also can be achieved by a hospital belonging to the “late majority” and to see whether such benefits are sustained, using report turnaround time (RTAT) as an indicator. Activity-related data was retrieved from the radiology information system (RIS) over a 2-year period. The median RTAT for preliminary reports was initially reduced from 12 to 2 h then increased to 3 h. For final reports, the median RTAT was initially reduced from 23 to 13 h then gradually reverted back to 22 h. Innovators and early adopters demonstrate not only that positive results can be achieved but also the importance of involving key personnel. We believe that such involvement and the focus on wider organizational concerns are important when introducing PACS to the late majority, both for achieving and sustaining positive results.
Radiology information systems (RIS); radiology reporting; radiology workflow; PACS; cost effectiveness; medical informatics applications
Successfully introducing a new technology in a health-care setting is not a walk in the park. Many barriers need to be overcome, not only technical and financial but also human barriers. In this study, we focus on the human barriers to health-care information systems’ implementation. We monitored the acceptance of a Picture Archiving and Communication System (PACS) by radiologists and hospital physicians in a large Belgian university hospital. Hereto, questionnaires were taken pre-implementation (T1) and 1 year after the radiology department stopped printing film (T2). The framework we used to perform the study was the Unified Theory of Acceptance and Use of Technology. Main findings were that both groups were positive toward PACS prior to the introduction and that each group was even more positive at T2 with extensive PACS experience. In general, the ratings of the radiologists were higher than those of the physicians, as the radiologists experienced more of the benefits of PACS and had to use PACS throughout the day. Two factors were salient for predicting users’ intention to use PACS: the usefulness of PACS (performance expectancy) and the availability of support of any kind (facilitating conditions). The results show that our approach was successful. Both radiologists and physicians give evidence of an excellent level of user acceptance. We can conclude that the implementation of PACS into our hospital has succeeded.
PACS; acceptance testing; computers in medicine; radiology workflow; UTAUT; attitude; university hospital
The study investigates the effect of a substantial dose reduction on the variability of lung nodule volume measurements by assessing and comparing nodule volumes using a dedicated semiautomated segmentation software on ultralow-dose computed tomography (ULD-CT) and standard-dose computed tomography (SD-CT) data. In 20 patients, thin-slice chest CT datasets (1 mm slice thickness; 20% reconstruction overlap) were acquired at ultralow-dose (120 kV, 5 mAs) and at standard-dose (120 kV, 75 mAs), respectively, and analyzed using the segmentation software OncoTREAT (MeVis, Bremen, Germany; version 1.3). Interobserver variability of volume measurements of 202 solid pulmonary nodules (mean diameter 11 mm, range 3.2–44.5 mm) was calculated for SD-CT and ULD-CT. With respect to interobserver variability, the 95% confidence interval for the relative differences in nodule volume in the intrascan analysis was measured with −9.7% to 8.3% (mean difference −0.7%) for SD-CT and with −12.6% to 12.4% (mean difference −0.2%) for ULD-CT. In the interscan analysis, the 95% confidence intervals for the differences in nodule volume ranged with −25.1% to −23.4% and 26.2% to 28.9% (mean difference 1.4% to 2.1%) dependent on the combination of readers and scans. Intrascan interobserver variability of volume measurements was comparable for ULD-CT and SD-CT data. The calculated variability of volume measurements in the interscan analysis was similar to the data reported in the literature for CT data acquired with equal radiation dose. Thus, the evaluated segmentation software provides nodule volumetry that appears to be independent of the dose level with which the CT source dataset is acquired.
Chest CT; lung neoplasms; segmentation; computer-aided diagnosis (CAD); radiation dose
We describe the development of software that allows and automates the routine inclusion of nondigital paper-based data directly into DICOM examinations. No human intervention is required. The software works by allowing the direct faxing of nondigital paper-based patient data directly into DICOM imaging examinations and is added as the first series in the examination. The software is effective in any typical PACS/DICOM server environment.
DICOM conversion; DICOM server; image to DICOM conversion; TIFF to DICOM; JPEG to DICOM; DICOM barcode; DICOM workflow
Although accurate information on thoracolumbar bone structure is essential when computed tomography (CT) images are examined, there is no automated method of labeling all the vertebrae and ribs on a CT scan. We are developing a computer-aided diagnosis system that labels ribs and thoracolumbar vertebrae automatically and have evaluated its accuracy. A candidate bone was extracted from the CT image volume data by pixel thresholding and connectivity analysis. All non-bony anatomical structures were removed using a linear discriminate of distribution of CT values and anatomical characteristics. The vertebrae were separated from the ribs on the basis of their distances from the centers of the vertebral bodies. Finally, the thoracic cage and lumbar vertebrae were extracted, and each vertebra was labeled with its own anatomical number by histogram analysis along the craniocaudal midline. The ribs were labeled in a similar manner, based on location data. Twenty-three cases were used for accuracy comparison between our method and the radiologist’s. The automated labeling of the thoracolumbar vertebrae was concordant with the judgments of the radiologist in all cases, and all but the first and second ribs were labeled correctly. These two ribs were frequently misidentified, presumably because of pericostal anatomical clutter or high densities of contrast material in the injected veins. We are confident that this system can contribute usefully as part of a picture archiving and communication system workstation, though further technical improvement is required for identification of the upper ribs.
Computer-aided diagnosis; bone labeling; CT; PACS; ribs
Grid has emerged recently as an integration infrastructure for sharing and coordinated use of diverse resources in dynamic, distributed environment. In this paper, we present a prototype system for integration of heterogeneous medical databases based on Grid technology, which can provide a uniform access interface and efficient query mechanism to different medical databases. After presenting the architecture of the prototype system that employs corresponding Grid services and middleware technologies, we make an analysis on its basic functional components including OGSA-DAI, metadata model, transaction management, and query processing in detail, which cooperate with each other to enable uniform accessing and seamless integration of the underlying heterogeneous medical databases. Then, we test effectiveness and performance of the system through a query instance, analyze the experiment result, and make a discussion on some issues relating to practical medical applications. Although the prototype system has been carried out and tested in a simulated hospital information environment at present, the underlying principles are applicable to practical applications.
Grid; medical database; OGSA-DAI; metadata
This paper presents a radiological collaborative tool capable of direct manipulation of Digital Imaging and Communications in Medicine (DICOM) images on both sides, and also recording and reenacting of a recorded session. A special collaborative application protocol formerly developed was extended and used as basis for the development of collaborative session recording and playback processes. The protocol is used today for real-time radiological meetings through the Internet. This new standard for collaborative sessions makes possible other uses for the protocol, such as asynchronous collaborative sessions, decision regulation, auditing, and educational applications. Experimental results are given which compare this protocol with other popular collaborative approaches. Comparison of these results shows that the proposed protocol performs much better than other approaches when run under controlled conditions.
Collaborative session; session playback; session recording; telemedicine; teleradiology; DICOM workstation
Ideally, medical x-ray imaging systems should be designed to deliver maximum image quality at an acceptable radiation risk to the patient. Quality assurance procedures are employed to ensure that these standards are maintained. A quality control protocol for direct digital radiography (DDR) systems is described and discussed. Software to automatically process and analyze the required images was developed. In this paper, the initial results obtained on equipment of different DDR manufacturers were reported. The protocol was developed to highlight even small discrepancies in standard operating performance.
Quality control; direct digital radiography; automatic software; quality assurance; automated measurement; image quality analysis
Doppler ultrasound is an important noninvasive diagnostic tool for cardiovascular diseases. Modern ultrasound imaging systems utilize spectral Doppler techniques for quantitative evaluation of blood flow velocities, and these measurements play a crucial rule in the diagnosis and grading of arterial stenosis. One drawback of Doppler-based blood flow quantification is that the operator has to manually specify the angle between the Doppler ultrasound beam and the vessel orientation, which is called the Doppler angle, in order to calculate flow velocities. In this paper, we will describe a computer vision approach to automate the Doppler angle estimation. Our approach starts with the segmentation of blood vessels in ultrasound color Doppler images. The segmentation step is followed by an estimation technique for the Doppler angle based on a skeleton representation of the segmented vessel. We conducted preliminary clinical experiments to evaluate the agreement between the expert operator’s angle specification and the new automated method. Statistical regression analysis showed strong agreement between the manual and automated methods. We hypothesize that the automation of the Doppler angle will enhance the workflow of the ultrasound Doppler exam and achieve more standardized clinical outcome.
Automated measurement; automated object detection; biomedical image analysis; clinical application; computer analysis; computer; vision; image analysis; ultrasound; color Doppler; vascular
A growing number of clinicians, educators, researchers, and others use digital images in their work and search for them via image retrieval systems. Yet, this area of information retrieval is much less understood and developed than searching for text-based content, such as biomedical literature and its derivations. The goal of the ImageCLEF medical image retrieval task (ImageCLEFmed) is to improve understanding and system capability in search for medical images. In this paper, we describe the development and use of a medical image test collection designed to facilitate research with image retrieval systems and their users. We also provide baseline results with the new collection and describe them in the context of past research with portions of the collection.
Medical image retrieval; imageCLEF; test collection; recall; precision
Recent advances in technology have significantly changed radiology workflow. The main focus of these changes has been the transition from hard copy film to digital imaging. The next transition will be a “paperless” transformation. Web-based versions of the current paper-based patient safety and history questionnaires were created using PHP and MySQL. Two rounds of usability testing using volunteers were completed using tablet PCs. Volunteers were comprised of ten individuals. Ages of volunteers ranged from 27 to 60 years, and there were eight males and two females. The majority of users had at least a Master’s degree and was considered to have a computer experience level of a programmer. Eighty percent of the users agreed that the web-based questionnaires and tablet PCs were easy to use. Text input through the writing recognition window and scrolling proved to be the least usable sections of the questionnaires. The new web-based system was found to be a very usable system by our participants. The questionnaires were easy to use, easy to navigate, and easy to read. Individual elements such as radio buttons and checkboxes did not fair as well but were due to their small size. Difficulty with the writing recognition interface is an inherent issue with the Windows XP Tablet Edition operating system.
Usability; paperless; filmless; tablet PC; workflow
To solve the problems of image displays in filmless radiology conferences for the purpose of teaching, we made an experimental design of a conference system with dual 50-in. plasma monitors for displaying larger images and a shared folder containing shortcuts to images for quick display during conferences on the desktop of each client computer in a picture archival and communication system. The image quality of the monitors was evaluated using the TG18-QC test pattern. The display time of images was measured in 20 cases when the shared folder was used and when it was not. Monitor screen size and image quality, operability, display time of images, and overall impression given by the system were evaluated subjectively by five radiologists. Although the image quality of the monitor was not as high as that of the high-resolution monitors used for diagnostic radiology, its performance was good enough for teaching. The average display time using the shared folder (2.6 ± 0.39 s) was significantly shorter than without it (16.9 ± 5.04 s; p = 2.85 × 10−6). Despite the need for certain improvements in monitor size and in the operability of the system, the radiologists considered the system suitable for radiology teaching conferences. We believe that this system is useful for institutions that intend to introduce a filmless system for filmless radiology teaching conferences.
Digital radiography; PACS; conferences; monitors; computer applications
Given the ease of alteration of digital data, integrity verification and tamper detection for medical images are becoming ever more important. In this paper, instead of using the conventional irreversible block-based watermarking approach to achieve tamper localization, we propose to incorporate such functionality into the region-based lossless watermarking scheme. This is achieved by partitioning an image into certain non-overlapping regions and appending the associated local authentication information directly into the watermark payload. A region of authentication, which can be flexibly specified by the user, is partitioned into small regions in a multilevel hierarchical manner. Such hierarchical structure allows the user to easily adjust the localization accuracy, and makes the tamper detection efficient. Experimental results demonstrate the effectiveness of tamper localization.
Watermarking; security; integrity; image authentication; tamper localization; telemedicine; PACS; ROI
The purpose of our study was to demonstrate the use of Natural Language Processing (Leximer), along with Online Analytic Processing, (NLP-OLAP), for extraction of finding trends in a large radiology practice. Prior studies have validated the Natural Language Processing (NLP) program, Leximer for classifying unstructured radiology reports based on the presence of positive radiology findings (FPOS) and negative radiology findings (FNEG). The FPOS included new relevant radiology findings and any change in status from prior imaging. Electronic radiology reports from 1995–2002 and data from analysis of these reports with NLP-Leximer were saved in a data warehouse and exported to a multidimensional structure called the Radcube. Various relational queries on the data in the Radcube were performed using OLAP technique. Thus, NLP-OLAP was applied to determine trends of FPOS in different radiology exams for different patient and examination attributes. Pivot tables were exported from NLP-OLAP interface to Microsoft Excel for statistical analysis. Radcube allowed rapid and comprehensive analysis of FPOS and FNEG trends in a large radiology report database. Trends of FPOS were extracted for different patient attributes such as age groups, gender, clinical indications, diseases with ICD codes, patient types (inpatient, ambulatory), imaging characteristics such as imaging modalities, referring physicians, radiology subspecialties, and body regions. Data analysis showed substantial differences between FPOS rates for different imaging modalities ranging from 23.1% (mammography, 49,163/212,906) to 85.8% (nuclear medicine, 93,852/109,374; p < 0.0001). In conclusion, NLP-OLAP can help in analysis of yield of different radiology exams from a large radiology report database.
Natural language processing; Online Analytical Processing (OLAP); data mining
From 2002–2004, the Lung Screening Study (LSS) of the National Lung Screening Trial (NLST) enrolled 34,614 participants, aged 55–74 years, at increased risk for lung cancer due to heavy cigarette smoking. Participants, randomized to standard chest X-ray (CXR) or computed tomography (CT) arms at ten screening centers, received up to three imaging screens for lung cancer at annual intervals. Participant medical histories and radiologist-interpreted screening results were transmitted to the LSS coordinating center, while all images were retained at local screening centers. From 2005–2007, all CT exams were uniformly de-identified and delivered to a central repository, the CT Image Library (CTIL), on external hard drives (94%) or CD/DVD (5.9%), or over a secure Internet connection (0.1%). Of 48,723 CT screens performed, only 176 (0.3%) were unavailable (lost, corrupted, compressed) while 48,547 (99.7%) were delivered to the CTIL. Described here is the experience organizing, implementing, and adapting the clinical-trial workflow surrounding the image retrieval, de-identification, delivery, and archiving of available LSS–NLST CT exams for the CTIL, together with the quality assurance procedures associated with those collection tasks. This collection of CT exams, obtained in a specific, well-defined participant population under a common protocol at evenly spaced intervals, and its attending demographic and clinical information, are now available to lung-disease investigators and developers of computer-aided-diagnosis algorithms. The approach to large scale, multi-center trial CT image collection detailed here may serve as a useful model, while the experience reported should be valuable in the planning and execution of future equivalent endeavors.
Cancer detection; chest CT; clinical trial; computed tomography; de-identification; lung diseases; digital image management; image database; image libraries; national lung screening trial; lung screening study; CT image library
New technological advancements including multislice CT scanners and functional MRI, have dramatically increased the size and number of digital images generated by medical imaging departments. Despite the fact that the cost of storage is dropping, the savings are largely surpassed by the increasing volume of data being generated. While local area network bandwidth within a hospital is adequate for timely access to imaging data, efficiently moving the data between institutions requires wide area network bandwidth, which has a limited availability at a national level. A solution to address those issues is the use of lossy compression as long as there is no loss of relevant information. The goal of this study was to determine levels at which lossy compression can be confidently used in diagnostic imaging applications. In order to provide a fair assessment of existing compression tools, we tested and compared the two most commonly adopted DISCOM compression algorithms: JPEG and JPEG-2000. We conducted an extensive pan-Canadian evaluation of lossy compression applied to seven anatomical areas and five modalities using two recognized techniques: objective methods or diagnostic accuracy and subjective assessment based on Just Noticeable Difference. By incorporating both diagnostic accuracy and subjective evaluation techniques, enabled us to define a range of compression for each modality and body part tested. The results of our study suggest that at low levels of compression, there was no significant difference between the performance of lossy JPEG and lossy JPEG 2000, and that they are both appropriate to use for reporting on medical images. At higher levels, lossy JPEG proved to be more effective than JPEG 2000 in some cases, mainly neuro CT. More evaluation is required to assess the effect of compression on thin slice CT. We provide a table of recommended compression ratios for each modality and anatomical area investigated, to be integrated in the Canadian Association of Radiologists standard for the use of lossy compression in medical imaging.
Compression; JPEG2000; digital imaging; lossy compression; JPEG
In this work, two different approaches are proposed for region of interest (ROI) segmentation using transrectal ultrasound (TRUS) images. The two methods aim to extract informative features that are able to characterize suspicious regions in the TRUS images. Both proposed methods are based on multi-resolution analysis that is characterized by its high localization in both the frequency and the spatial domains. Being highly localized in both domains, the proposed methods are expected to accurately identify the suspicious ROIs. On one hand, the first method depends on a Gabor filter that captures the high frequency changes in the image regions. On the other hand, the second method depends on classifying the wavelet coefficients of the image. It is shown in this paper that both methods reveal details in the ROIs which correlate with their pathological representations. It was found that there is a good match between the regions identified using the two methods, a result that supports the ability of each of the proposed methods to mimic the radiologist’s decision in identifying suspicious regions. Studying two ROI segmentation methods is important since the only available dataset is the radiologist’s suspicious regions, and there is a need to support the results obtained by either one of the proposed methods. This work is mainly a preliminary proof of concept study that will ultimately be expanded to a larger scale study whose aim will be introducing an assisting tool to help the radiologist identify the suspicious regions.
Biomedical image analysis; decision support; computer-aided diagnosis (CAD); image processing
To reduce variability of Cobb angle measurement for scoliosis assessment, a computerized method was developed. This method automatically measured the Cobb angle on spinal posteroanterior radiographs after the brightness and the contrast of the image were adjusted, and the top and bottom of the vertebrae were selected. The automated process started with the edge detection of the vertebra by Canny edge detector. After that, the fuzzy Hough transform was used to find line structures in the vertebral edge images. The lines that fitted to the endplates of vertebrae were identified by selecting peaks in Hough space under the vertebral shape constraints. The Cobb angle was then calculated according to the directions of these lines. A total of 76 radiographs were respectively analyzed by an experienced surgeon using the manual measurement method and by two examiners using the proposed method twice. Intraclass correlation coefficients (ICC) showed high agreement between automatic and manual measurements (ICCs > 0.95). The mean absolute differences between automatic and manual measurements were less than 5°. In the interobserver analyses, ICCs were higher than 0.95, and mean absolute differences were less than 5°. In the intraobserver analyses, ICCs were 0.985 and 0.978, respectively, for each examiner, and mean absolute differences were less than 3°. These results demonstrated the validity and reliability of the proposed method.
Cobb angle; scoliosis; fuzzy Hough transform (FHT); shape prior; radiograph
A method is proposed for 3D segmentation and quantification of the masseter muscle from magnetic resonance (MR) images, which is often performed in pre-surgical planning and diagnosis. Because of a lack of suitable automatic techniques, a common practice is for clinicians to manually trace out all relevant regions from the image slices which is extremely time-consuming. The proposed method allows significant time savings. In the proposed method, a patient-specific masseter model is built from a test dataset after determining the dominant slices that represent the salient features of the 3D muscle shape from training datasets. Segmentation is carried out only on these slices in the test dataset, with shape-based interpolation then applied to build the patient-specific model, which serves as a coarse segmentation of the masseter. This is first refined by matching the intensity distribution within the masseter volume against the distribution estimated from the segmentations in the dominant slices, and further refined through boundary analysis where the homogeneity of the intensities of the boundary pixels is analyzed and outliers removed. It was observed that the left and right masseter muscles’ volumes in young adults (28.54 and 27.72cm3) are higher than those of older (ethnic group removed) adults (23.16 and 22.13cm3). Evaluation indicates good agreement between the segmentations and manual tracings, with average overlap indexes for the left and right masseters at 86.6% and 87.5% respectively.
Segmentation; masseter; masticatory muscle; patient-specific; matching distribution