Healthcare Imaging

Research and innovation addressing today's greatest health challenges.

 

List of Publications

Publications

Title Authors Conference/Journal Year Area
Improving the Performance and Explainability of Mammogram Classifiers with Local Annotations L. Ness, E.Barkan, M.Ozery-Flato accepted to iMIMIC Workshop, MICCAI 2020 2020 Breast Imaging
Multi-task learning for detection and classification of cancer in screening mammography Maria V. Sainz de Cea, Karl Diedrich, Ran Bakalo, Lior Ness, David Richmond MICCAI 2020 2020 Breast Imaging
Radiomics for predicting response to neoadjuvant chemotherapy treatment in breast cancer Simona Rabinovici-Cohen, Tal Tlusty, Ami Abutbul, Kari Antila, Xosé Fernandez, Beatriz Grandal Rejo, Efrat Hexter, Oliver Hijano Cubelos, Abed Khateeb, Juha Pajula, Shaked Perek Proceedings of SPIE 11318 Breast Imaging, Houston, Texas, United States, 2020 2020 Breast Imaging
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms Thomas Schaffter, Diana SM Buist, Christoph I Lee, Yaroslav Nikulin, Dezso Ribli, Yuanfang Guan, William Lotter, Zequn Jie, Hao Du, Sijia Wang, Jiashi Feng, Mengling Feng, Hyo-Eun Kim, Francisco Albiol, Alberto Albiol, Stephen Morrell, Zbigniew Wojna, Mehmet Eren Ahsen, Umar Asif, Antonio Jimeno Yepes, Shivanthan Yohanandan, Simona Rabinovici-Cohen, Darvin Yi, Bruce Hoff, Thomas Yu, Elias Chaibub Neto, Daniel L Rubin, Peter Lindholm, Laurie R Margolies, Russell Bailey McBride, Joseph H Rothstein, Weiva Sieh, Rami Ben-Ari, Stefan Harrer, Andrew Trister, Stephen Friend, Thea Norman, Berkman Sahiner, Fredrik Strand, Justin Guinney, Gustavo Stolovitzky, Lester Mackey, Joyce Cahoon, Li Shen, Jae Ho Sohn, Hari Trivedi, Yiqiu Shen, Ljubomir Buturovic, Jose Costa Pereira, Jaime S Cardoso, Eduardo Castro, Karl Trygve Kalleberg, Obioma Pelka, Imane Nedjar, Krzysztof J Geras, Felix Nensa, Ethan Goan, Sven Koitka, Luis Caballero, David D Cox, Pavitra Krishnaswamy, Gaurav Pandey, Christoph M Friedrich, Dimitri Perrin, Clinton Fookes, Bibo Shi, Gerard Cardoso Negrie, Michael Kawczynski, Kyunghyun Cho, Can Son Khoo, Joseph Y Lo, A Gregory Sorensen, Hwejin Jung Journal of the American Medical Association (JAMA) Network Open, 2020 2020 Breast Imaging
Multimodal Prediction of Breast Cancer Relapse Prior to Neoadjuvant Chemotherapy Treatment Simona Rabinovici-Cohen, Ami Abutbul, Xosé Fernandez, Oliver Hijano Cubelos, Shaked Perek, Tal Tlusty PRIME-MICCAI Workshop, 2020 2020 Breast Imaging
The case of missed cancers: Applying AI as a radiologist’s safety net Michal Chorev,Yoel Shoshan, Adam Spiro, Shaked Naor, Alon Hazan, Vesna Barros, Iuliana Weinstein, Esma Herzel, Varda Shalev, Michal Guindy,Michal Rosen-Zvi MICCAI 2020 2020 Breast Imaging, Machine Learning
DDxNet: a deep learning model for automatic interpretation of electronic health records, electrocardiograms and electroencephalograms Deepta Rajan, Jayaraman J. Thiagarajan, Sameeksha Katoch and Andreas Spanias Nature Scientific Reports 2020 Deep Learning for Clinical Time-Series
Automatic localization of lung opacity in chest CT images - A Real-world Study Yiting Xie, Deepta Rajan, Larissa Schudlo et al. SPIE 2020 Segmentation of Lung Opacities in CT
Self-Training with Improved Regularization for Sample-Efficient Chest X-Ray Classification Deepta Rajan, Jayaraman J. Thiagarajan, Alexandros Karargyris, Satyananda Kashyap SPIE 2020 Semi-Supervised Learning for Chest X-rays
Improving Reliability of Clinical Models using Prediction Calibration Jayaraman J Thiagarajan, Bindya Venkatesh, Deepta Rajan, Prasanna Sattigeri MICCAI UNSURE Workshop 2020 Interpretability and Uncertainty Quantification
Automatic Diagnosis of Pulmonary Embolism Using an Attention-guided Framework: A Large-scale Study Luyao Shi, Deepta Rajan, Shafiq Abedin, Manikanta Srikar Yellapragada, David Beymer, Ehsan Dehghan MIDL (PMLR) 2020 Attention-guided Segmentation for Cardiac CT
Pi-PE: A pipeline for pulmonary embolism detection using sparsely annotated 3D CT images Deepta Rajan, David Beymer, Shafiqul Abedin, Ehsan Dehghan NeurIPS ML4H (PMLR) 2019 Multiple Instance Learning with Weak Annotations for Cardiac CT
Leveraging medical visual question answering with supporting facts Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade, Alexis Asseman, Ahmet S Ozcan CLEF (Working Notes) 2019 Medical VQA for Radiology
Understanding Behavior of Clinical Models under Domain Shifts Jayaraman J. Thiagarajan, Deepta Rajan, Prasanna Sattigeri KDD Data Science for Health 2019 (Best Paper) Domain Adaptation in Electronic Health Records Analysis
Generalization studies of neural network models for cardiac disease detection using limited channel ecg Deepta Rajan, David Beyner, Girish Narayanan IEEE CinC 2018 ECG Cardiac Disease Detection
A generative modeling approach to limited channel ECG classification Deepta Rajan et al. IEEE EMBC 2018 ECG Abnormality Detection
Attend and diagnose: Clinical time series analysis using attention models Deepta Rajan et al. AAAI 2018 Clinical Time-Series (Electronic Health Records)
Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms Akselrod-Ballin, Ayelet; Chorev, Michal; Shoshan, Yoel; Spiro, Adam; Hazan, Alon; Melamed, Roie; Barkan, Ella; Herzel, Esma; Naor, Shaked; Karavani, Ehud; Koren, Gideon; Goldschmidt, Yaara; Shalev, Varda; Rosen-Zvi, Michal; Guindy, Michal Radiology 2019 Breast Imaging
Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography Akselrod-Ballin, Ayelet; Karlinsky, Leonid.; Hazan, Alon; Bakalo, Ran; Horesh, Ami Ben; Shoshan, Yoel; Barkan, Ella Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support 2017 Breast Imaging
Semi-supervised learning with generative adversarial networks for chest X-ray classification with ability of data domain adaptation Madani, A.; Moradi, M.; Karargyris, A.; Syeda-Mahmood, T. 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) 2018 Chest Xray
Hybrid Mass Detection in Breast MRI Combining Unsupervised Saliency Analysis and Deep Learning Amit, Guy; Hadad, Omer; Alpert, Sharon; Tlusty, Tal; Gur, Yaniv; Ben-Ari, Rami; Hashoul, Sharbell Medical Image Computing and Computer Assisted Intervention − MICCAI 2017, Springer International Publishing 2017 Breast Imaging
Mammogram Classification with Ordered Loss Ben-Ari, Rami; Shoshan, Yoel; Tlusty, Tal Artificial Intelligence in Medicine, Springer International Publishing 2019 Breast Imaging
Mammogram Classification and Abnormality Detection from Nonlocal Labels using Deep Multiple Instance Neural Network Choukroun, Yoni; Bakalo, Ran; Ben-Ari, Rami; Akselrod-Ballin, Ayelet; Barkan, Ella; Kisilev, Pavel Eurographics Workshop on Visual Computing for Biology and Medicine 2017 Breast Imaging
A deep learning framework for context-aware mitotic activity estimation in whole slide images Pushpak Pati; Raul Catena; Orcun Goksel; Maria Gabrani SPIE Medical Imaging 2019 Digital Pathology
A Fast and Scalable Pipeline for Stain Normalization of Whole-Slide Images in Histopathology | springerprofessional.de Milos Stanisavljevic, Andreea Anghel, Nikolaos Papandreou, Sonali Andani, Pushpak Pati, Jan Hendrik Ruschoff, Peter Wild, Maria Gabrani, Haralampos Pozidis ECCV 2018 Workshops 2018 Digital Pathology
Medical sieve: a cognitive assistant for radiologists and cardiologists Syeda-Mahmood, T.; Walach, E.; Beymer, D.; Gilboa-Solomon, F.; Moradi, M.; Kisilev, P.; Kakrania, D.; Compas, C.; Wang, H.; Negahdar, R.; Cao, Y.; Baldwin, T.; Guo, Y.; Gur, Y.; Rajan, D.; Zlotnick, A.; Rabinovici-Cohen, S.; Ben-Ari, R.; Guy, Amit; Prasanna, P.; Morey, J.; Boyko, O.; Hashoul, S. Medical Imaging 2016: Computer-Aided Diagnosis 2016 Cardiac/Chest/Brain/General Medical Imaging
A Structure-Aware Convolutional Neural Network for Skin Lesion Classification Thandiackal, Kevin; Goksel, Orcun OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis 2018 Dermatology Imaging
Maximizing AUC with Deep Learning for Classification of Imbalanced Mammogram Datasets Sulam, J.; Ben-Ari, R.; Kisilev, P. Proceedings of the Eurographics Workshop on Visual Computing for Biology and Medicine 2017 Breast Imaging
Deep positive-unlabeled learning for region of interest localization in breast tissue images Pati, Pushpak; Andani, Sonali; Pediaditis, Matthew; Viana, Matheus Palhares; Rüschoff, Jan Hendrik; Wild, Peter; Gabrani, Maria Medical Imaging 2018: Digital Pathology 2018 Breast Imaging
A feature agnostic approach for glaucoma detection in OCT volumes Maetschke, Stefan; Antony, Bhavna; Ishikawa, Hiroshi; Wollstein, Gadi; Schuman, Joel; Garnavi, Rahil PLOS ONE 2019 Retinal Imaging
Retinal optical coherence tomography image enhancement via deep learning Halupka, Kerry J.; Antony, Bhavna J.; Lee, Matthew H.; Lucy, Katie A.; Rai, Ravneet S.; Ishikawa, Hiroshi; Wollstein, Gadi; Schuman, Joel S.; Garnavi, Rahil Biomedical optics express, vol 9 issue 12 pages 6205-6221 2018 Retinal Imaging
Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images Using Bayesian Deep Learning Sedai, Suman; Antony, Bhavna; Mahapatra, Dwarikanath; Garnavi, Rahil Computational Pathology and Ophthalmic Medical Image Analysis, Springer International Publishing 2018 Retinal Imaging
Deep Multiscale Convolutional Feature Learning for Weakly Supervised Localization of Chest Pathologies in X-ray Images Sedai, Suman; Mahapatra, Dwarikanath; Ge, Zongyuan; Chakravorty, Rajib; Garnavi, Rahil Machine Learning in Medical Imaging, Springer International Publishing 2018 Chest Xray
Deformable medical image registration using generative adversarial networks Mahapatra, D.; Antony, B.; Sedai, S.; Garnavi, R. 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) 2018 Retinal and Cardiac
Deep Semantic Instance Segmentation of Tree-Like Structures Using Synthetic Data Halupka, K.; Garnavi, R.; Moore, S. 2019 IEEE Winter Conference on Applications of Computer Vision (WACV) 2019 Cardiac/Chest/Brain/General Medical Imaging
Building a Benchmark Dataset and Classifiers for Sentence-Level Findings in AP Chest X-rays Syeda-Mahmood, Tanveer; Ahmad, Hassan M.; Ansari, Nadeem; Gur, Yaniv; Kashyap, Satyananda; Karargyris, Alexandros; Moradi, Mehdi; Pillai, Anup; Sheshadri, Karthik; Wang, Weiting; Wong, Ken C. L.; Wu, Joy T. arXiv:1906.09336 [cs], accepted to ISBI 2019 Chest Xray
Boosting the rule-out accuracy of deep disease detection using class weight modifiers Karargyris, Alexandros; Wong, Ken C. L.; Wu, Joy T.; Moradi, Mehdi; Syeda-Mahmood, Tanveer arXiv:1906.09354 [cs, eess], accepted to ISBI 2019 Chest Xray
Artificial intelligence for point of care radiograph quality assessment Kashyap, Satyananda; Moradi, Mehdi; Karargyris, Alexandros; Wu, Joy T.; Morris, Michael; Saboury, Babak; Siegel, Eliot; Syeda-Mahmood, Tanveer Medical Imaging 2019: Computer-Aided Diagnosis 2019 Chest Xray
Age prediction using a large chest x-ray dataset Karargyris, A.; Kashyap, S.; Wu, J. T.; Sharma, A.; Moradi, M.; Syeda-Mahmood, T. Medical Imaging 2019: Computer-Aided Diagnosis 2019 Chest Xray
Disease Detection in Weakly Annotated Volumetric Medical Images using a Convolutional LSTM Network Braman, Nathaniel; Beymer, David; Dehghan, Ehsan arXiv:1812.01087 [cs], Medical Imaging Meets NeurIPS Workshop at NeurIPS 2018 2018 Lung Imaging
Lung tissue characterization for emphysema differential diagnosis using deep convolutional neural networks Negahdar, Mohammadreza; Beymer, David Medical Imaging 2019: Computer-Aided Diagnosis 2019 Lung Imaging
Automated Detection and Type Classification of Central Venous Catheters in Chest X-Rays Subramanian, Vaishnavi; Wang, Hongzhi; Wu, Joy T.; Wong, Ken C. L.; Sharma, Arjun; Syeda-Mahmood, Tanveer arXiv:1907.01656 [cs, eess], accepted to MICCAI 2019 Chest Xray
Uncertainty guided semisupervised segmentation of retinal layers in OCT images Suman Sedai, Bhavna Antony,  Hiroshi Ishikawa,  Joel Schuman, Gadi Wollstein, Ravneet Rai, Katie Jones, Rahil Garnavi accepted to MICCAI 2019 Retinal Imaging
SegNAS3D: Network Architecture Search with Derivative-Free Global Optimization for 3D Image Segmentation Ken CL Wong, Mehdi Moradi accepted to MICCAI 2019 Cardiac/Chest/Brain/General Medical Imaging
Deep Network Anatomy Segmentation with Limited Annotations Using Auxiliary Labels Ahmed Harouni, Hongzhi Wang, Tanveer Syeda-Mahmood, David Beymer ISBI 2019 Cardiac/Chest/Brain/General Medical Imaging
Learning from Longitudinal Mammography Studies Perek S, Ness L, Amit M, Barkan E, Amit G accepted to MICCAI 2019 Breast Imaging
Accelerated ML-assisted Tumor Detection in High-Resolution Histopathology Images Ioannou N, Stanisavljevic M, Anghel A, Papandreou N, Andani S, Hendrick Ruschoff J, Wild P, Gabrani M, Pozidis H accepted to MICCAI 2019 Digital Pathology
Mammography Dual View Mass Correspondence S. Perek, A. Hazan, E. Barkan, A. Akselrod Ballin accepted to KDD 2018 Breast Imaging
Unsupervised clustering of mammograms for outlier detection and breast density estimation R. Ben-Ari, T. Tlusty and G.Amit accepted to ICPR 2018 Breast Imaging
A CNN based method for Automated Mass Detection and classification in Mammograms Akselrod-Ballin, A., Karlinsky, L., Alpert, S., Hasoul, S., Ben-Ari, R. and Barkan, E. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization 2017 Breast Imaging
Mammogram Classification and Abnormality Detection from Nonlocal Labels using Deep Multiple Instance Neural Networks Y. Choukroun, R. Bakalo, R. Ben-Ari, A. Akselrod-Ballin, E. Barkan and P. Kisilev EG VCBM 2017 Breast Imaging
Weakly Supervised DNN with AUC Loss for Classification of Imbalanced Mammogram Datasets J. Sulam, R. Ben-Ari and P. Kisilev EG VCBM 2017 Breast Imaging
Hybrid Mass Detection in Breast MRI combining Unsupervised Saliency Analysis and Deep Learning G. Amit, O.Hadad,  S.Alpert, T. Tlusty, Y. Gur, R. Ben-Ari, S.Hashoul MICCAI 2017 Breast Imaging
Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography Akselrod-Ballin, A., Karlinsky, L., Alpert, S., Hasoul, S., Ben-Ari, R. and Barkan, E. MICCAI - DLMIA 2017 Breast Imaging
Domain Specific CNN’s for Detection of Architectural distortion in Mammograms R. Ben-Ari, A. Akselrod-Ballin, L. Karlinsky, S. Hashoul ISBI 2017 Breast Imaging
Classification of Breast Lesion using Cross-Modal Deep Learning O. Hadad, R. Bakalo, R. Ben-Ari, S. Hashoul, G. Amit ISBI 2017 Breast Imaging
Classification of Breast MRI Lesions using Small-Size Training Sets: Comparison of Deep Learning Approaches. G. Amit, R. Ben-Ari , O. Hadada , E. Monovicha , N. Granot , S. Hashoul SPIE 2017 Breast Imaging
Medical image description using multi-task-loss CNN P. Kisilev, E. Sason, S. Hashoul, E. Barkan, E. Walach MICCAI DLMIA 2016 Breast Imaging
A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography Akselrod-Ballin, A., Karlinsky, L., Alpert, S., Hasoul, S., Ben-Ari, R. and Barkan, E MICCAI DLMIA 2016 Breast Imaging
Semantic Object Boundary Detection Using Convolutional Neural Networks with Regression Output P. Kisilev and E. Sason IBM  Deep Learning Workshop 2016 Breast Imaging
Computational mammography using deep neural networks Dubrovina, A., Kisilev, P., Ginsburg, B., Hashoul, S. and Kimmel, R. Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, pp.1-5. 2016 Breast Imaging
Deformable image registration using generative adversial networks Dwarkanath Mahapatra, Bhavna Antony, Suman Sedai, Rahil Garnavi ISBI 2018 Retinal Imaging
Semi-supervised Segmentation of Optic Cup in Retinal Fundus Images Using Aariational Autoencoder S. Sedai, D. Mahapatra, R. Garnavi, MICCAI 2017 Retinal Imaging
Image Super Resolution Using Generative Adversarial Networks and Local Saliency Maps for Retinal Image Analysis D. Mahapatra, B. Bozorgtabar, R. Garnavi MICCAI 2017 Retinal Imaging
A novel hybrid approach for severity assessment of diabetic retinopathy in colour fundus images P. Roy, R. Tennakoon, K. Cao, S. Sedai, D. Mahapatra, S. Maetschke, and R. Garnavi ISBI 2017 Retinal Imaging
Multi-Stage Segmentation of the Fovea in Retinal Fundus Images Using Fully Convolutional Neural Networks Suman Sedai, Ruwan Tennakoon, Pallab Roy, Khoa Cao, Rahil Garnavi ISBI 2017 Retinal Imaging
Retinal Image Quality Classification Using Saliency Maps And CNNs Mahapatra, D., Roy, P.K., Sedai, S. and Garnavi, R. In International Workshop on Machine Learning in Medical Imaging (pp. 172-179). Springer International Publishing. 2016 Retinal Imaging
Quality Classification for DR Screening Using Convolutional Neural Networks R. Tennakoon, D. Mahapatra, R.Garnavi MICCAI-OMIA 2016 Retinal Imaging
Automatic Eye Type Detection in Retinal Fundus Image Using Fusion of Transfer Learning and Anatomical Features. Roy, P.K., Chakravorty, R., Sedai, S., Mahapatra, D. and Garnavi, R. In Digital Image Computing: Techniques and Applications (DICTA), 2016 International Conference on (pp. 1-7). IEEE. 2016 Retinal Imaging
GraspNet: an efficient convolutional neural network for real-time grasp detection for low powered devices U. Asif, J. Tang, S. Harrer accepted full paper at IJCAI 2018 Epilepsy (and Neurobionics) EEG
A portable low-cost EEG motor imagery-based brain-computer interface S. Yohanandan, I. Kiral-Kornek, B. Mashford, J. Tang, U. Asif, S. Harrer accepted full paper at IEEE Engineering in Medicine and Biology Conference (EMBC) 2018 Epilepsy (and Neurobionics) EEG
Deep learning enabled automatic abnormal EEG identification S. Roy, I. Kiral-Kornek, S. Harrer accepted full paper at IEEE Engineering in Medicine and Biology Conference (EMBC) 2018 Epilepsy (and Neurobionics) EEG
ChronoNet: A deep recurrent neural network for abnormal EEG identification S. Roy, I. Kiral-Kornek, S. Harrer arXiv 2018 Epilepsy (and Neurobionics) EEG
A mobile and tunable seizure prediction system using deep-learning Isabell Kiral-Kornek, Subhrajit Roy, Ewan Nurse, Benjamin S. Mashford, Philippa Karoly, Daniel Payne, Susmita Saha, Terence O’Brien, David B. Grayden, Mark Cook, Dean Freestone, Stefan Harrer in Proceedings of the Annual Meeting of the American Epilepsy Society 2017 Epilepsy (and Neurobionics) EEG
Epileptic seizure prediction using big data and deep learning: toward a mobile system Isabell Kiral-Kornek, Subhrajit Roy, Ewan Nurse, Benjamin S. Mashford,  Philippa Karoly, Thomas Carrol, Daniel Payne, Susmita Saha, Steven Baldassano, Terence O’Brien, David B. Grayden, Mark Cook, Dean Freestone, Stefan Harrer EBioMedicine (a Lancet journal) 2017 Epilepsy (and Neurobionics) EEG
Improving classification accuracy of feedforward neural networks for spiking neuromorphic chips Jimeno Yepes, A., Tang, J., Mashford, B.S. IJCAI 2017 Epilepsy (and Neurobionics) EEG
Deep-learning-based analysis of EEG-data for developing real-time brain-machine interfaces B. S. Mashford, A. Jimeno Yepes, I. Kiral-Kornek, J. Tang. S. Harrer IBM Journal of Research and Development 2017 Epilepsy (and Neurobionics) EEG
TrueNorth-enabled Real-time Classification of EEG Data for Brain-Computer Interfacing I. Kiral-Kornek, D. Mendis, E, S. Nurse, B. S. Mashford, D, R. Freestone, D, B. Grayden, S. Harrer In Proceedings of the IEEE Engineering in Medicine and Biology Conference (EMBC) 2017 Epilepsy (and Neurobionics) EEG
Decoding EEG and LFP signals using deep learning: heading TrueNorth Nurse, E., Mashford, B.S., Yepes, A.J., Kiral-Kornek, I., Tang, J., Deligianni, L., Grayden, D. Freestone, D.R, and Harrer, S. In Proceedings of the ACM International Conference on Computing Frontiers (ACM), (pp. 259-266) 2016 Epilepsy (and Neurobionics) EEG
From Wearables to THINKables - Deep Learning, Nano-biosensors and the Next Generation of Mobile Devices Harrer, S., Kiral-Kornek, I., Kerr, R., Mashford, B., Tang, J., Yepes, A.J. and Deligianni, H., 2016 White Paper, ICONN 2016 Epilepsy (and Neurobionics) EEG
Role of big data and machine learning in diagnostic decision support in radiology T. Syeda-Mahmood in Journal of American College of Radiology, Volume 15, Issue 3, Part B, Pages 569–576 2018 Cardiac/Chest/Brain/General Medical Imaging
Echocardiagraphy segmentation based on a shape-guided deformable model driven by a fully convolutional network prior Gopalkrishna Veni, Mehdi Moradi, Hakan Bulu, Girish Narayan, Tanveer Syeda-Mahmood ISBI 2018 Cardiac/Chest/Brain/General Medical Imaging
Detecting Anomalies from Echocardiography using Multi-View Regression of Clinical Measurements Allen Lu, Ehsan Dehghan, Mehdi Moradi, Tanveer Syeda-Mahmood ISBI 2018 Cardiac/Chest/Brain/General Medical Imaging
Semi-supervised learning with generative adversarial networks for chest X-ray classification with ability of data domain adaptation Ali Madani, Mehdi Moradi, Alexandros Karargyris, Tanveer Syeda-Mahmood ISBI 2018 Cardiac/Chest/Brain/General Medical Imaging
Universtal multimodal deep network for classification and segmentation of medical images Ahmed Harouni, Alexandros Karargyris, Mohammadreza Negahdar, David Beymer, Tanveer Syeda- Mahmood ISBI 2018 Cardiac/Chest/Brain/General Medical Imaging
Rapid annotation of 3D medical imaging datasets using registration-based interpolation and adaptive slice selection  Honzhi Wang, Prasanth Prasanna, M.D., Tanveer Syeda-Mahmood ISBI 2018 Cardiac/Chest/Brain/General Medical Imaging
Segmentation of anatomical structures in cardiac CTA using multi-label V-Net Hui Tang, Mehdi Moradi, Ahmed El harouni, Hongzhi Wang, Prasanth Prasanna, Gopal Veni, Tanveer Syeda-Mahmood SPIE 2018 Cardiac/Chest/Brain/General Medical Imaging
Chest x-ray generation and data augmentation for cardiovascular abnormality classification Ali Madani, Tanveer Syeda-Mahmood, Alexandros Karargyris SPIE 2018 Cardiac/Chest/Brain/General Medical Imaging
Building Disease Detection Algorithms with Very Small Number of Positive Samples C. L. (Ken) Wong, A. Karargyris, T. Syeda-Mahmood, M. Moradi MICCAI 2017 Cardiac/Chest/Brain/General Medical Imaging
A multi-atlas approach to region of interest detection for medical image classification H. Wang, M. Moradi, Y. Gur, P. Prasanna, T. Syeda-Mahmood MICCAI 2017 Cardiac/Chest/Brain/General Medical Imaging
Towards An Efficient Way of Building Annotated Medical Image Collections for Big Data Studies Y. Gur, M. Moradi, H. Bulu, Y. Guo, C. Compas, T. Syeda-Mahmood LABELS 2017 Cardiac/Chest/Brain/General Medical Imaging
Automatic Labeling of Continuous Wave Doppler Images Based on Combined Image and Sentence Networks M. Moradi, Y. Guo, Y. Gur, T. Syeada-Mahmood ISBI 2017 Cardiac/Chest/Brain/General Medical Imaging
A Cross-Modality Neural Network Transform for Semi-Automatic Medical Image Annotation M. Moradi, Y. Guo, Y. Gur, M. Negahdar, and T. Syeda-Mahmood MICCAI 2016 Cardiac/Chest/Brain/General Medical Imaging
A hybrid learning approach for semantic labeling of cardiac CT slices and recognition of body position   Mehdi Moradi, Yaniv Gur, Hongzhi Wang, Prasanth Prasanna, Tanveer Syeda-Mahmood IEEE 13th International Symposium on Biomedical Imaging (ISBI), pp. 1418--1421 2016 Cardiac/Chest/Brain/General Medical Imaging
Skin Disease Recognition Using Deep Saliency Features and Multimodal Learning of Dermoscopy and Clinical Images Z. Ge, R. Chakravorty, A. Bowling R. Garnavi MICCAI 2017. Dermatology Imaging
Exploiting Local and Generic Features for Skin Lesions Classification Z.Ge, S.Demyanov, S.Bozorgtabar, R. Chakravorty, A. Bowling, R. Garnavi. IEEE ISBI 2017 Dermatology Imaging
Tree-loss function for training neural networks on weakly-labelled datasets S. Demyanov, R. Chakravorty, Z. Ge, et al. IEEE ISBI 2017 Dermatology Imaging
Investigating Deep Side Layers For Skin Lesion Segmentation B. Bozorgtabar, Z. Ge, R. Chakravorty, et al. IEEE ISBI 2017 Dermatology Imaging
Skin lesion segmentation using deep convolution networks guided by local unsupervised learning B. Bozorgtabar, S. Sedai, P. Roy, R. Garnavi IBM R&D Journal 2017 Dermatology Imaging
Classification of dermoscopy patterns using deep convolutional neural networks S. Demyanov, R. Chakravorty, M. Abedini, R. Garnavi IEEE ISBI 2016 Dermatology Imaging
Computational Immunohistochemistry: Recipes for Standardization of Immunostaining N. M. Arar, P. Pati,  A. Kashyap, A. Fomitcheva Khartchenko, G. Kaigala, M. Gabrani MICCAI 2017 Digital Pathology 
Heterogeneity Characterization of Immunohistochemically Stained Tissue using Convolutional Autoencoder E. Zerhouni, et. Al Proceedings of SPIE 2017 Digital Pathology 
Wide Residual Networks for Mitosis Detection E. Zerhouni, et. Al Proceedings of IEEE 14th International Symposium on Biomedical Imaging (ISBI) 2017 Digital Pathology 
Disease Grading of Heterogeneous Tissue using Convolutional Autoencoder E. Zerhouni, et. Al Proceedings of IEEE 14th International Symposium on Biomedical Imaging (ISBI) 2017 Digital Pathology 
Computational Processing of Histological Images E. Zerhouni et al. ERCIM News, Vol. 108, pp. 14-15 2017 Digital Pathology 
Image-based computational quantification and visualization of genetic alterations and tumour heterogeneity Zhong, Q. et. al. Scientic Reports 6(24146) 2016 Digital Pathology 
Big Data takes on Prostate cancer Zerhouni, E., Prisacari, B., Zhong, Q., Wild, P., Gabrani, M. ERCIM News, 104, pp. 34-35 2016 Digital Pathology 
Deciphering protein signatures using color, morphological, and topological analysis of immunohistochemically stained human tissues  Erwan Zerhouni, Bogdan Prisacari, Qing Zhong, Peter Wild, Maria Gabrani Proceedings of SPIE Vol. 9791, 97910T 2016 Digital Pathology 
A computational framework for disease grading using protein signatures  Erwan Zerhouni, Bogdan Prisacari, Qing Zhong, Peter Wild, Maria Gabrani 13th IEEE International Symposium on Biomedical Imaging, (ISBI 2016), Prague, Czech Republic, April 13-16, 1401-1404 2016 Digital Pathology 
Hierarchical Deep Learning Ensemble to Automate the Classification of Breast Cancer Pathology Reports by ICD-O Topography W. Saib, et. Al accepted to KDD Workshops 2018 Textual Data Analysis
TaGiTeD: Predictive Task Guided Tensor Decomposition for Representation Learning from Electronic Health Records Yang,K., Li,X., Liu,H., Mei,J., Xie,G., Zhao,J., Xie,B., Wang,F. AAAI 2017 Structured Patients Data
Deep Diabetologist: Learning to Prescribe Hypoglycemia Medications with Hierarchical Recurrent Neural Networks J Mei, S Zhao, F Jin, L Zhang, H Liu, X Li MedInfo 2017 Structured Patients Data
Risk prediction with electronic health records: A deep learning approach Y.Cheng, F.Wang, P.Zhang, and J. Hu. In Proceedings of the SIAM International Conference on Data Mining (pp. 432-440) 2016 Structured Patients Data
Exploiting Convolutional Neural Network for Risk Prediction with Medical Feature Embedding. Z. Che, Y. Cheng, Z. Sun,  and Y. Liu. NIPS workshop on ML for Health 2016 Structured Patients Data
Deep State Space Models for Computational Phenotyping. S. Ghosh, Y. Cheng, and Z. Sun. ICHI 2016 Structured Patients Data
Measuring Patient Similarities via A Deep Architecture with Medical Concept Embedding Z.Zhe, C.Yin, B.Qian, Y.Cheng, J.Wei, F.Wang ICDM 2016 Structured Patients Data
A Deep Learning based Method for Similar Patient Question Retrieval in Chinese G Tang, Y Ni, G Xie, X Fan, Y Shi MedInfo 2017 Social Textual Data
NER for Medical Entities in Twitter using Sequence to Sequence Neural Networks Jimeno Yepes, A., and MacKinlay, A. Australasian Language Technology Association Workshop 2016 Social Textual Data
Deep Belief Networks and Biomedical Text Categorisation Jimeno Yepes, A., MacKinlay, A., Bedo, J., Garnavi, R., and Chen, Q. Australasian Language Technology Association Workshop 2014 Social Textual Data
An efficient multi-scale data representation method for lung nodule false positive reduction using convolutional neural networks Dario A.B.Oliveira, Matheus P. Viana ISBI 2018 Lung Imaging
Lung Nodule Malignancy Prediction Using Multi-task Convolutional Neural Network Xiuli Li, Yueying Kao, Wei Shen, Xiang Li, Guotong Xie SPIE Medical Imaging 2017 Lung Imaging
Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data R.Anirudh, et al. SPIE 2016 Lung Imaging
Exploring Transfer Learning for Gastrointestinal Bleeding Detection on Small-size Imbalanced Endoscopy Images Xiuli Li, Hao Zhang, Xiaolu Zhang, Hao Liu and Guotong Xie IEEE Engineering in Medicine and Biology Society (EMBC) 2017 Gastrointestinal Imaging