Artykuły udostępnione publicznie: - Jayashree Kalpathy-CramerWięcej informacji
Niedostępne w żadnym miejscu: 12
Towards practical unsupervised anomaly detection on retinal images
K Ouardini, H Yang, B Unnikrishnan, M Romain, C Garcin, H Zenati, ...
Domain Adaptation and Representation Transfer and Medical Image Learning …, 2019
Upoważnienia: US National Science Foundation, US National Institutes of Health, A*Star …
Multimodal medical image retrieval: image categorization to improve search precision
J Kalpathy-Cramer, W Hersh
Proceedings of the international conference on Multimedia information …, 2010
Upoważnienia: US National Institutes of Health
Analysis of underlying causes of inter-expert disagreement in retinopathy of prematurity diagnosis
E Ataer-Cansizoglu, J Kalpathy-Cramer, S You, K Keck, D Erdogmus, ...
Methods of information in medicine 54 (01), 93-102, 2015
Upoważnienia: US National Institutes of Health
Contour-based shape representation using principal curves
E Ataer-Cansizoglu, E Bas, J Kalpathy-Cramer, GC Sharp, D Erdogmus
Pattern Recognition 46 (4), 1140-1150, 2013
Upoważnienia: US National Institutes of Health
Use of risk-based cervical screening programs in resource-limited settings
RB Perkins, DL Smith, J Jeronimo, NG Campos, JC Gage, N Hansen, ...
Cancer Epidemiology 84, 102369, 2023
Upoważnienia: US National Institutes of Health
Using media fusion and domain dimensions to improve precision in medical image retrieval
S Radhouani, J Kalpathy-Cramer, S Bedrick, B Bakke, W Hersh
Multilingual Information Access Evaluation II. Multimedia Experiments: 10th …, 2010
Upoważnienia: Swiss National Science Foundation, US National Institutes of Health
A GMM-based feature extraction technique for the automated diagnosis of retinopathy of prematurity
V Bolón-Canedo, E Ataer-Cansizoglu, D Erdogmus, J Kalpathy-Cramer, ...
2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI), 1498-1501, 2015
Upoważnienia: US National Institutes of Health
Sequential neural networks for biologically informed glioma segmentation
A Beers, K Chang, J Brown, E Gerstner, B Rosen, J Kalpathy-Cramer
Medical Imaging 2018: Image Processing 10574, 807-816, 2018
Upoważnienia: US National Institutes of Health
Improving early precision in the ImageCLEF medical retrieval task
S Bedrick, S Radhouani, J Kalpathy–Cramer
ImageCLEF: Experimental Evaluation in Visual Information Retrieval, 397-413, 2010
Upoważnienia: US National Institutes of Health
Assessing robustness of a deep-learning model for COVID-19 classification on chest radiographs
M Shenouda, A Kaveti, I Flerlage, J Kalpathy-Cramer, ML Giger, ...
Medical Imaging 2023: Computer-Aided Diagnosis 12465, 75-80, 2023
Upoważnienia: US National Institutes of Health
Relevance Judgments for Image Retrieval Evaluation
J Kalpathy–Cramer, S Bedrick, W Hersh
ImageCLEF: Experimental Evaluation in Visual Information Retrieval, 63-80, 2010
Upoważnienia: US National Institutes of Health
Papers Abstracts
A Mahajan, UR Baid, N Sable, S Talbar, S Rane, A Moyadi, ...
International Journal of Neurooncology 2 (1), 30-74, 2019
Upoważnienia: Department of Science & Technology, India
Dostępne w jakimś miejscu: 270
3D Slicer as an image computing platform for the Quantitative Imaging Network
A Fedorov, R Beichel, J Kalpathy-Cramer, J Finet, JC Fillion-Robin, ...
Magnetic resonance imaging 30 (9), 1323-1341, 2012
Upoważnienia: US National Institutes of Health
The multimodal brain tumor image segmentation benchmark (BRATS)
BH Menze, A Jakab, S Bauer, J Kalpathy-Cramer, K Farahani, J Kirby, ...
IEEE transactions on medical imaging 34 (10), 1993-2024, 2014
Upoważnienia: Swiss National Science Foundation, US National Institutes of Health, German …
Introduction to machine learning, neural networks, and deep learning
RY Choi, AS Coyner, J Kalpathy-Cramer, MF Chiang, JP Campbell
Translational vision science & technology 9 (2), 14-14, 2020
Upoważnienia: US National Science Foundation, US National Institutes of Health
Consensus recommendations for a standardized Brain Tumor Imaging Protocol in clinical trials
BM Ellingson, M Bendszus, J Boxerman, D Barboriak, BJ Erickson, ...
Neuro-oncology 17 (9), 1188-1198, 2015
Upoważnienia: US National Institutes of Health
Automated diagnosis of plus disease in retinopathy of prematurity using deep convolutional neural networks
JM Brown, JP Campbell, A Beers, K Chang, S Ostmo, RVP Chan, J Dy, ...
JAMA ophthalmology 136 (7), 803-810, 2018
Upoważnienia: US National Institutes of Health
The RSNA pediatric bone age machine learning challenge
SS Halabi, LM Prevedello, J Kalpathy-Cramer, AB Mamonov, A Bilbily, ...
Radiology 290 (2), 498-503, 2019
Upoważnienia: US National Institutes of Health, National Institute for Health Research, UK
Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging
K Chang, HX Bai, H Zhou, C Su, WL Bi, E Agbodza, VK Kavouridis, ...
Clinical Cancer Research 24 (5), 1073-1081, 2018
Upoważnienia: US National Institutes of Health, National Natural Science Foundation of China
Radiomics in brain tumor: image assessment, quantitative feature descriptors, and machine-learning approaches
M Zhou, J Scott, B Chaudhury, L Hall, D Goldgof, KW Yeom, M Iv, Y Ou, ...
American Journal of Neuroradiology 39 (2), 208-216, 2018
Upoważnienia: US National Institutes of Health
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