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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/28884381/development-of-a-computer-aided-differential-diagnosis-system-to-distinguish-between-usual-interstitial-pneumonia-and-non-specific-interstitial-pneumonia-using-texture-and-shape-based-hierarchical-classifiers-on-hrct-images
#1
SangHoon Jun, BeomHee Park, Joon Beom Seo, SangMin Lee, Namkug Kim
A computer-aided differential diagnosis (CADD) system that distinguishes between usual interstitial pneumonia (UIP) and non-specific interstitial pneumonia (NSIP) using high-resolution computed tomography (HRCT) images was developed, and its results compared against the decision of a radiologist. Six local interstitial lung disease patterns in the images were determined, and 900 typical regions of interest were marked by an experienced radiologist. A support vector machine classifier was used to train and label the regions of interest of the lung parenchyma based on the texture and shape characteristics...
September 7, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28842816/single-center-experience-implementing-the-loinc-rsna-radiology-playbook-for-adult-abdomen-pelvis-ct-and-mr-procedures-using-a-semi-automated-method
#2
Ranjit S Sandhu, James Shin, Kenneth C Wang, George Shih
The LOINC-RSNA Radiology Playbook represents the future direction of standardization for radiology procedure names. We developed a software solution ("RadMatch") utilizing Python 2.7 and FuzzyWuzzy, an open-source fuzzy string matching algorithm created by SeatGeek, to implement the LOINC-RSNA Radiology Playbook for adult abdomen and pelvis CT and MR procedures performed at our institution. Execution of this semi-automated method resulted in the assignment of appropriate LOINC numbers to 86% of local CT procedures...
August 25, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28840386/medical-image-retrieval-using-multi-texton-assignment
#3
Qiling Tang, Jirong Yang, Xianfu Xia
In this paper, we present a multi-texton representation method for medical image retrieval, which utilizes the locality constraint to encode each filter bank response within its local-coordinate system consisting of the k nearest neighbors in texton dictionary and subsequently employs spatial pyramid matching technique to implement feature vector representation. Comparison with the traditional nearest neighbor assignment followed by texton histogram statistics method, our strategies reduce the quantization errors in mapping process and add information about the spatial layout of texton distributions and, thus, increase the descriptive power of the image representation...
August 24, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28840365/radiology-and-enterprise-medical-imaging-extensions-remix
#4
Barbaros S Erdal, Luciano M Prevedello, Songyue Qian, Mutlu Demirer, Kevin Little, John Ryu, Thomas O'Donnell, Richard D White
Radiology and Enterprise Medical Imaging Extensions (REMIX) is a platform originally designed to both support the medical imaging-driven clinical and clinical research operational needs of Department of Radiology of The Ohio State University Wexner Medical Center. REMIX accommodates the storage and handling of "big imaging data," as needed for large multi-disciplinary cancer-focused programs. The evolving REMIX platform contains an array of integrated tools/software packages for the following: (1) server and storage management; (2) image reconstruction; (3) digital pathology; (4) de-identification; (5) business intelligence; (6) texture analysis; and (7) artificial intelligence...
August 24, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28840360/minimizing-barriers-in-learning-for-on-call-radiology-residents-end-to-end-web-based-resident-feedback-system
#5
Hailey H Choi, Jennifer Clark, Ann K Jay, Ross W Filice
Feedback is an essential part of medical training, where trainees are provided with information regarding their performance and further directions for improvement. In diagnostic radiology, feedback entails a detailed review of the differences between the residents' preliminary interpretation and the attendings' final interpretation of imaging studies. While the on-call experience of independently interpreting complex cases is important to resident education, the more traditional synchronous "read-out" or joint review is impossible due to multiple constraints...
August 24, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28808803/a-prototype-educational-model-for-hepatobiliary-interventions-unveiling-the-role-of-graphic-designers-in-medical-3d-printing
#6
Ramin Javan, Merissa N Zeman
In the context of medical three-dimensional (3D) printing, in addition to 3D reconstruction from cross-sectional imaging, graphic design plays a role in developing and/or enhancing 3D-printed models. A custom prototype modular 3D model of the liver was graphically designed depicting segmental anatomy of the parenchyma containing color-coded hepatic vasculature and biliary tree. Subsequently, 3D printing was performed using transparent resin for the surface of the liver and polyamide material to develop hollow internal structures that allow for passage of catheters and wires...
August 14, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28808802/interpretation-and-diplomacy-aspects-of-authority-and-care-in-imaging-reports
#7
Werner A Golder
Whereas the creativity and intellectual power of the radiologist are measured against his/her written report, the value of the message will not only be judged by the precision of the medical statement. The same result can be attributed to different words. Numerous common and accidental factors exert influence on the decision on what is said and what is not said, how it is assessed and what is ignored. The less certain a diagnosis is and the less favourable its possible consequences are, the more subtleties and periphrases are to be expected within the report...
August 14, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28808792/using-natural-language-processing-of-free-text-radiology-reports-to-identify-type-1-modic-endplate-changes
#8
Hannu T Huhdanpaa, W Katherine Tan, Sean D Rundell, Pradeep Suri, Falgun H Chokshi, Bryan A Comstock, Patrick J Heagerty, Kathryn T James, Andrew L Avins, Srdjan S Nedeljkovic, David R Nerenz, David F Kallmes, Patrick H Luetmer, Karen J Sherman, Nancy L Organ, Brent Griffith, Curtis P Langlotz, David Carrell, Saeed Hassanpour, Jeffrey G Jarvik
Electronic medical record (EMR) systems provide easy access to radiology reports and offer great potential to support quality improvement efforts and clinical research. Harnessing the full potential of the EMR requires scalable approaches such as natural language processing (NLP) to convert text into variables used for evaluation or analysis. Our goal was to determine the feasibility of using NLP to identify patients with Type 1 Modic endplate changes using clinical reports of magnetic resonance (MR) imaging examinations of the spine...
August 14, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28799133/tablets-for-image-review-and-communication-in-daily-routine-of-orthopedic-surgeons-an-evaluation-study
#9
Sven Y Vetter, Svenja Schüler, Matthes Hackbusch, Michael Müller, Benedict Swartman, Marc Schnetzke, Paul Alfred Grützner, Jochen Franke
Medical images are essential in modern traumatology and orthopedic surgery. Access to images is often cumbersome due to a limited number of workstations. Moreover, due to the tremendous increase of data, the time to review or to communicate images has also become limited. One approach to overcome these problems is to make use of modern mobile devices, like tablet computers, to facilitate image access and associated workflows. Ten orthopedic surgeons were equipped with an Apple iPad mini 2 and specialized viewing software for medical images...
August 10, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28785874/statistical-geometrical-features-for-microaneurysm-detection
#10
Arati Manjaramkar, Manesh Kokare
Automated microaneurysm (MA) detection is still an open challenge due to its small size and similarity with blood vessels. In this paper, we present a novel method which is simple, efficient, and real-time for segmenting and detecting MA in color fundus images (CFI). To do this, a novel set of features based on statistics of geometrical properties of connected regions, that can easily discriminate lesion and non-lesion pixels are used. For large-scale evaluation proposed method is validated on DIARETDB1, ROC, STARE, and MESSIDOR dataset...
August 7, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28785873/residual-deep-convolutional-neural-network-predicts-mgmt-methylation-status
#11
Panagiotis Korfiatis, Timothy L Kline, Daniel H Lachance, Ian F Parney, Jan C Buckner, Bradley J Erickson
Predicting methylation of the O6-methylguanine methyltransferase (MGMT) gene status utilizing MRI imaging is of high importance since it is a predictor of response and prognosis in brain tumors. In this study, we compare three different residual deep neural network (ResNet) architectures to evaluate their ability in predicting MGMT methylation status without the need for a distinct tumor segmentation step. We found that the ResNet50 (50 layers) architecture was the best performing model, achieving an accuracy of 94...
August 7, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28785872/checklist-for-a-radiology-information-system-go-live
#12
Ron Gefen, Hani H Abujudeh
This article highlights the experience of a single center institution undergoing a change in radiology information system (RIS) software platforms, transitioning to an electronic medical record-RIS driven workflow. Ten planning and execution topics with recommendations are presented in checklist form from the radiology department perspective. The build process of creating a site specific RIS takes many months, beginning with the organization of a steering committee. On Go-Live, several checklist items are offered to help streamline the troubleshooting process and improve communication throughout the radiology department...
August 7, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28766028/a-hybrid-2d-3d-user-interface-for-radiological-diagnosis
#13
Veera Bhadra Harish Mandalika, Alexander I Chernoglazov, Mark Billinghurst, Christoph Bartneck, Michael A Hurrell, Niels de Ruiter, Anthony P H Butler, Philip H Butler
This paper presents a novel 2D/3D desktop virtual reality hybrid user interface for radiology that focuses on improving 3D manipulation required in some diagnostic tasks. An evaluation of our system revealed that our hybrid interface is more efficient for novice users and more accurate for both novice and experienced users when compared to traditional 2D only interfaces. This is a significant finding because it indicates, as the techniques mature, that hybrid interfaces can provide significant benefit to image evaluation...
August 1, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28762098/preprocessing-prediction-of-advanced-algorithms-for-medical-imaging
#14
Bella Fadida-Specktor
Advanced medical imaging algorithms (such as bone removal, vessel segmentation, or a lung nodule detection) can provide extremely valuable information to the radiologists, but they might sometimes be very time consuming. Being able to run the algorithms in advance can be a possible solution. However, we do not know which algorithm to run on a given dataset before it is actually used. It is possible to manually insert matching rules for preprocessing algorithms, but it requires high maintenance and does not work well in practice...
July 31, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28752323/bone-tumor-diagnosis-using-a-na%C3%A3-ve-bayesian-model-of-demographic-and-radiographic-features
#15
Bao H Do, Curtis Langlotz, Christopher F Beaulieu
Because many bone tumors have a variety of appearances and are uncommon, few radiologists develop sufficient expertise to guide optimal management. Bayesian inference can guide decision-making by computing probabilities of multiple diagnoses to generate a differential. We built and validated a naïve Bayes machine (NBM) that processes 18 demographic and radiographic features. We reviewed over 1664 analog radiographic cases of bone tumors and selected 811 cases (66 diagnoses) for annotation using a quantitative imaging platform...
July 27, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28752322/redefining-the-practice-of-peer-review-through-intelligent-automation-part-2-data-driven-peer-review-selection-and-assignment
#16
Bruce I Reiner
In conventional radiology peer review practice, a small number of exams (routinely 5% of the total volume) is randomly selected, which may significantly underestimate the true error rate within a given radiology practice. An alternative and preferable approach would be to create a data-driven model which mathematically quantifies a peer review risk score for each individual exam and uses this data to identify high risk exams and readers, and selectively target these exams for peer review. An analogous model can also be created to assist in the assignment of these peer review cases in keeping with specific priorities of the service provider...
July 27, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28730549/creation-and-curation-of-the-society-of-imaging-informatics-in-medicine-hackathon-dataset
#17
Marc Kohli, James J Morrison, Judy Wawira, Matthew B Morgan, Jason Hostetter, Brad Genereaux, Mohannad Hussain, Steve G Langer
In order to support innovation, the Society of Imaging Informatics in Medicine (SIIM) elected to create a collaborative computing experience called a "hackathon." The SIIM Hackathon has always consisted of two components, the event itself and the infrastructure and resources provided to the participants. In 2014, SIIM provided a collection of servers to participants during the annual meeting. After initial server setup, it was clear that clinical and imaging "test" data were also needed in order to create useful applications...
July 20, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28695342/thyroid-nodule-classification-in-ultrasound-images-by-fine-tuning-deep-convolutional-neural-network
#18
Jianning Chi, Ekta Walia, Paul Babyn, Jimmy Wang, Gary Groot, Mark Eramian
With many thyroid nodules being incidentally detected, it is important to identify as many malignant nodules as possible while excluding those that are highly likely to be benign from fine needle aspiration (FNA) biopsies or surgeries. This paper presents a computer-aided diagnosis (CAD) system for classifying thyroid nodules in ultrasound images. We use deep learning approach to extract features from thyroid ultrasound images. Ultrasound images are pre-processed to calibrate their scale and remove the artifacts...
July 10, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28685320/can-laws-be-a-potential-pet-image-texture-analysis-approach-for-evaluation-of-tumor-heterogeneity-and-histopathological-characteristics-in-nsclc
#19
Seyhan Karacavus, Bülent Yılmaz, Arzu Tasdemir, Ömer Kayaaltı, Eser Kaya, Semra İçer, Oguzhan Ayyıldız
We investigated the association between the textural features obtained from (18)F-FDG images, metabolic parameters (SUVmax, SUVmean, MTV, TLG), and tumor histopathological characteristics (stage and Ki-67 proliferation index) in non-small cell lung cancer (NSCLC). The FDG-PET images of 67 patients with NSCLC were evaluated. MATLAB technical computing language was employed in the extraction of 137 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), and Laws' texture filters...
July 6, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
https://www.readbyqxmd.com/read/28685319/workflow-for-visualization-of-neuroimaging-data-with-an-augmented-reality-device
#20
Christof Karmonik, Timothy B Boone, Rose Khavari
Commercial availability of three-dimensional (3D) augmented reality (AR) devices has increased interest in using this novel technology for visualizing neuroimaging data. Here, a technical workflow and algorithm for importing 3D surface-based segmentations derived from magnetic resonance imaging data into a head-mounted AR device is presented and illustrated on selected examples: the pial cortical surface of the human brain, fMRI BOLD maps, reconstructed white matter tracts, and a brain network of functional connectivity...
July 6, 2017: Journal of Digital Imaging: the Official Journal of the Society for Computer Applications in Radiology
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