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Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology

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https://www.readbyqxmd.com/read/28429195/computer-assisted-diagnosis-system-for-breast-cancer-in-computed-tomography-laser-mammography-ctlm
#1
Afsaneh Jalalian, Syamsiah Mashohor, Rozi Mahmud, Babak Karasfi, M Iqbal Saripan, Abdul Rahman Ramli
Computed tomography laser mammography (Eid et al. Egyp J Radiol Nucl Med, 37(1): p. 633-643, 1) is a non-invasive imaging modality for breast cancer diagnosis, which is time-consuming and challenging for the radiologist to interpret the images. Some issues have increased the missed diagnosis of radiologists in visual manner assessment in CTLM images, such as technical reasons which are related to imaging quality and human error due to the structural complexity in appearance. The purpose of this study is to develop a computer-aided diagnosis framework to enhance the performance of radiologist in the interpretation of CTLM images...
April 20, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28405834/feasibility-study-of-a-generalized-framework-for-developing-computer-aided-detection-systems-a-new-paradigm
#2
Mitsutaka Nemoto, Naoto Hayashi, Shouhei Hanaoka, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa
We propose a generalized framework for developing computer-aided detection (CADe) systems whose characteristics depend only on those of the training dataset. The purpose of this study is to show the feasibility of the framework. Two different CADe systems were experimentally developed by a prototype of the framework, but with different training datasets. The CADe systems include four components; preprocessing, candidate area extraction, candidate detection, and candidate classification. Four pretrained algorithms with dedicated optimization/setting methods corresponding to the respective components were prepared in advance...
April 12, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28378032/computer-based-radiographic-quantification-of-joint-space-narrowing-progression-using-sequential-hand-radiographs-validation-study-in-rheumatoid-arthritis-patients-from-multiple-institutions
#3
Shota Ichikawa, Tamotsu Kamishima, Kenneth Sutherland, Jun Fukae, Kou Katayama, Yuko Aoki, Takanobu Okubo, Taichi Okino, Takahiko Kaneda, Satoshi Takagi, Kazuhide Tanimura
We have developed a refined computer-based method to detect joint space narrowing (JSN) progression with the joint space narrowing progression index (JSNPI) by superimposing sequential hand radiographs. The purpose of this study is to assess the validity of a computer-based method using images obtained from multiple institutions in rheumatoid arthritis (RA) patients. Sequential hand radiographs of 42 patients (37 females and 5 males) with RA from two institutions were analyzed by a computer-based method and visual scoring systems as a standard of reference...
April 4, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28374195/pathbot-a-radiology-pathology-correlation-dashboard
#4
Linda C Kelahan, Amit D Kalaria, Ross W Filice
Pathology is considered the "gold standard" of diagnostic medicine. The importance of radiology-pathology correlation is seen in interdepartmental patient conferences such as "tumor boards" and by the tradition of radiology resident immersion in a radiologic-pathology course at the American Institute of Radiologic Pathology. In practice, consistent pathology follow-up can be difficult due to time constraints and cumbersome electronic medical records. We present a radiology-pathology correlation dashboard that presents radiologists with pathology reports matched to their dictations, for both diagnostic imaging and image-guided procedures...
April 3, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28357589/use-of-a-web-based-calculator-and-a-structured-report-generator-to-improve-efficiency-accuracy-and-consistency-of-radiology-reporting
#5
Alexander J Towbin, C Matthew Hawkins
While medical calculators are common, they are infrequently used in the day-to-day radiology practice. We hypothesized that a calculator coupled with a structured report generator would decrease the time required to interpret and dictate a study in addition to decreasing the number of errors in interpretation. A web-based application was created to help radiologists calculate leg-length discrepancies. A time motion study was performed to evaluate if the calculator helped to decrease the time for interpretation and dictation of leg-length radiographs...
March 29, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28342044/3d-histopathology-a-lung-tissue-segmentation-workflow-for-microfocus-x-ray-computed-tomography-scans
#6
Lasse Wollatz, Steven J Johnston, Peter M Lackie, Simon J Cox
Lung histopathology is currently based on the analysis of 2D sections of tissue samples. The use of microfocus X-ray-computed tomography imaging of unstained soft tissue can provide high-resolution 3D image datasets in the range of 2-10 μm without affecting the current diagnostic workflow. Important details of structural features such as the tubular networks of airways and blood vessels are contained in these datasets but are difficult and time-consuming to identify by manual image segmentation. Providing 3D structures permits a better understanding of tissue functions and structural interrelationships...
March 24, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28342043/accuracy-validation-of-an-automated-method-for-prostate-segmentation-in-magnetic-resonance-imaging
#7
Maysam Shahedi, Derek W Cool, Glenn S Bauman, Matthew Bastian-Jordan, Aaron Fenster, Aaron D Ward
Three dimensional (3D) manual segmentation of the prostate on magnetic resonance imaging (MRI) is a laborious and time-consuming task that is subject to inter-observer variability. In this study, we developed a fully automatic segmentation algorithm for T2-weighted endorectal prostate MRI and evaluated its accuracy within different regions of interest using a set of complementary error metrics. Our dataset contained 42 T2-weighted endorectal MRI from prostate cancer patients. The prostate was manually segmented by one observer on all of the images and by two other observers on a subset of 10 images...
March 24, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28315069/toolkits-and-libraries-for-deep-learning
#8
REVIEW
Bradley J Erickson, Panagiotis Korfiatis, Zeynettin Akkus, Timothy Kline, Kenneth Philbrick
Deep learning is an important new area of machine learning which encompasses a wide range of neural network architectures designed to complete various tasks. In the medical imaging domain, example tasks include organ segmentation, lesion detection, and tumor classification. The most popular network architecture for deep learning for images is the convolutional neural network (CNN). Whereas traditional machine learning requires determination and calculation of features from which the algorithm learns, deep learning approaches learn the important features as well as the proper weighting of those features to make predictions for new data...
March 17, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28299488/measuring-the-benefits-of-a-regional-imaging-environment
#9
Jason Nagels, David Macdonald, Christine Coz
The use of central diagnostic imaging repositories (DIRs), that allow separate organizations with disparate PACS systems to seamlessly share patient data, is becoming more common; and as a result, the documentation of measurable benefits is a key deliverable to all stakeholders. Central DIRs and the implementation of foreign exam management (FEM) provide clinical users with the ability to seamlessly access DI exams and reports that originate from an outside location. FEM has been implemented to varying degrees across regional DIRs within Canada [1]...
March 15, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28275919/fully-automated-deep-learning-system-for-bone-age-assessment
#10
Hyunkwang Lee, Shahein Tajmir, Jenny Lee, Maurice Zissen, Bethel Ayele Yeshiwas, Tarik K Alkasab, Garry Choy, Synho Do
Skeletal maturity progresses through discrete phases, a fact that is used routinely in pediatrics where bone age assessments (BAAs) are compared to chronological age in the evaluation of endocrine and metabolic disorders. While central to many disease evaluations, little has changed to improve the tedious process since its introduction in 1950. In this study, we propose a fully automated deep learning pipeline to segment a region of interest, standardize and preprocess input radiographs, and perform BAA. Our models use an ImageNet pretrained, fine-tuned convolutional neural network (CNN) to achieve 57...
March 8, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28243865/a-new-medical-image-watermarking-technique-with-finer-tamper-localization
#11
Arda Ustubioglu, Guzin Ulutas
Medical imaging and information management systems require transmission of medical images over the Internet. Many image watermarking techniques have been proposed in recent years to ensure the integrity and authenticity of medical images transferred over insecure networks. In this work, we propose a new medical image watermarking technique to detect tampered regions on medical images with finer accuracy by authenticating 4 × 4 blocks and without restricting region of interest (ROI) size. The proposed method can mark a 4 × 4 pixel block if it has even one tampered pixel, while similar methods (which have no ROI size restriction) mark 8 × 8, 16 × 16, and 40 × 40 pixel blocks...
February 27, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28224381/an-ensemble-method-for-classifying-regional-disease-patterns-of-diffuse-interstitial-lung-disease-using-hrct-images-from-different-vendors
#12
Sanghoon Jun, Namkug Kim, Joon Beom Seo, Young Kyung Lee, David A Lynch
We propose the use of ensemble classifiers to overcome inter-scanner variations in the differentiation of regional disease patterns in high-resolution computed tomography (HRCT) images of diffuse interstitial lung disease patients obtained from different scanners. A total of 600 rectangular 20 × 20-pixel regions of interest (ROIs) on HRCT images obtained from two different scanners (GE and Siemens) and the whole lung area of 92 HRCT images were classified as one of six regional pulmonary disease patterns by two expert radiologists...
February 21, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28224380/who-you-gonna-call-automatically-connecting-radiologists-to-the-right-clinician
#13
Ross Filice
Contacting clinicians to convey critical results is a critical part of radiology workflow, but many obstacles prevent easy and timely communication. Integration of radiology applications and workflow with an EHR-based patient coverage database demonstrated subjective and objective improvement in radiologist workflow and satisfaction.
February 21, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28224379/nerves-of-steel-a-low-cost-method-for-3d-printing-the-cranial-nerves
#14
Ramin Javan, Duncan Davidson, Afshin Javan
Steady-state free precession (SSFP) magnetic resonance imaging (MRI) can demonstrate details down to the cranial nerve (CN) level. High-resolution three-dimensional (3D) visualization can now quickly be performed at the workstation. However, we are still limited by visualization on flat screens. The emerging technologies in rapid prototyping or 3D printing overcome this limitation. It comprises a variety of automated manufacturing techniques, which use virtual 3D data sets to fabricate solid forms in a layer-by-layer technique...
February 21, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28168529/imaging-properties-of-3d-printed-materials-multi-energy-ct-of-filament-polymers
#15
James Shin, Ranjit S Sandhu, George Shih
Clinical applications of 3D printing are increasingly commonplace, likewise the frequency of inclusion of 3D printed objects on imaging studies. Although there is a general familiarity with the imaging appearance of traditional materials comprising common surgical hardware and medical devices, comparatively less is known regarding the appearance of available 3D printing materials in the consumer market. This work detailing the CT appearance of a selected number of common filament polymer classes is an initial effort to catalog these data, to provide for accurate interpretation of imaging studies incidentally or intentionally including fabricated objects...
February 6, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28154988/computer-aided-reporting-of-chest-radiographs-efficient-and-effective-screening-in-the-value-based-imaging-era
#16
Michael Morris, Babak Saboury, Niketh Bandla, Christopher Toland, Christopher Meenan, Eliot Siegel, Jean Jeudy
In the post-PACS era, mammography is unique in adopting specialized ergonomic interfaces to improve efficiency in a high volume setting. Chest radiography is also a high volume area of radiology. The authors hypothesize that applying a novel interface for chest radiography interpretation and reporting could create high productivity while maintaining quality. A custom version of the ClearCanvas open source software, EzRad, was created with a workflow re-designed specifically for tuberculosis screening chest radiographs, which utilized standardized computer generated reports...
February 2, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28138796/javascript-access-to-dicom-network-and-objects-in-web-browser
#17
Ivan Drnasin, Mislav Grgić, Goran Gogić
Digital imaging and communications in medicine (DICOM) 3.0 standard provides the baseline for the picture archiving and communication systems (PACS). The development of Internet and various communication media initiated demand for non-DICOM access to PACS systems. Ever-increasing utilization of the web browsers, laptops and handheld devices, as opposed to desktop applications and static organizational computers, lead to development of different web technologies. The DICOM standard officials accepted those subsequently as tools of alternative access...
January 30, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28138795/3d-printing-prototypes-for-healthcare-professionals-creating-a-reciprocating-syringe
#18
Steven Rothenberg, Selwan Abdullah, Jeffrey Hirsch
3D printing (additive manufacturing) has been around since 1984, but interest in the technology has increased exponentially as it has become both accessible and inexpensive. The applications of the technology in healthcare are still being explored; however, initial forays have been encouraging. It has the potential to revolutionize the process of prototyping for healthcare professionals by democratizing the process and enhancing collaboration, making it cheaper to do iterative prototyping with little or no engineering experience...
January 30, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28025731/development-and-evaluation-of-a-semi-automated-segmentation-tool-and-a-modified-ellipsoid-formula-for-volumetric-analysis-of-the-kidney-in-non-contrast-t2-weighted-mr-images
#19
Hannes Seuss, Rolf Janka, Marcus Prümmer, Alexander Cavallaro, Rebecca Hammon, Ragnar Theis, Martin Sandmair, Kerstin Amann, Tobias Bäuerle, Michael Uder, Matthias Hammon
Volumetric analysis of the kidney parenchyma provides additional information for the detection and monitoring of various renal diseases. Therefore the purposes of the study were to develop and evaluate a semi-automated segmentation tool and a modified ellipsoid formula for volumetric analysis of the kidney in non-contrast T2-weighted magnetic resonance (MR)-images. Three readers performed semi-automated segmentation of the total kidney volume (TKV) in axial, non-contrast-enhanced T2-weighted MR-images of 24 healthy volunteers (48 kidneys) twice...
April 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28025730/automated-facial-recognition-of-computed-tomography-derived-facial-images-patient-privacy-implications
#20
Connie L Parks, Keith L Monson
The recognizability of facial images extracted from publically available medical scans raises patient privacy concerns. This study examined how accurately facial images extracted from computed tomography (CT) scans are objectively matched with corresponding photographs of the scanned individuals. The test subjects were 128 adult Americans ranging in age from 18 to 60 years, representing both sexes and three self-identified population (ancestral descent) groups (African, European, and Hispanic). Using facial recognition software, the 2D images of the extracted facial models were compared for matches against five differently sized photo galleries...
April 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
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