H. Greenspan

发表

Texture analysis via unsupervised and supervised learning

R. Chellappa, H. Greenspan, R. Goodman, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Serge J. Belongie, J. Malik, H. Greenspan, 1997, 1997 Proceedings IEEE Workshop on Content-Based Access of Image and Video Libraries.

Overcomplete steerable pyramid filters and rotation invariance

Pietro Perona, Hayit Greenspan, Serge J. Belongie, 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

Rotation invariant texture recognition using a steerable pyramid

Pietro Perona, Hayit Greenspan, Serge J. Belongie, 1994, Proceedings of the 12th IAPR International Conference on Pattern Recognition, Vol. 3 - Conference C: Signal Processing (Cat. No.94CH3440-5).

Multi-resolution image processing and learning for texture recognition and image enhancement

H. Greenspan, 1994 .

Finding Pictures of Objects in Large Collections of Images

Hayit Greenspan, Serge J. Belongie, Serge Belongie, 1996, Object Representation in Computer Vision.

Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying

Jitendra Malik, Hayit Greenspan, Serge J. Belongie, 2002, IEEE Trans. Pattern Anal. Mach. Intell..

GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification

Hayit Greenspan, Jacob Goldberger, Maayan Frid-Adar, 2018, Neurocomputing.

Automated retrieval of CT images of liver lesions on the basis of image similarity: method and preliminary results.

H. Greenspan, D. Rubin, S. Napel, 2010, Radiology.

Image enhancement by nonlinear extrapolation in frequency space

Hayit Greenspan, Charles H. Anderson, Sofia Akber, 2000, IEEE Trans. Image Process..

Combining image-processing and image compression schemes

H. Greenspan, M.-C. Lee, 1995 .

Region correspondence for image matching via EMD flow

H. Greenspan, Y. Rubner, G. Dvir, 2000, 2000 Proceedings Workshop on Content-based Access of Image and Video Libraries.

Learning Texture Discrimination Rules in a Multiresolution System

Rama Chellappa, Hayit Greenspan, Rodney M. Goodman, 1994, IEEE Trans. Pattern Anal. Mach. Intell..

Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique

Ronald M. Summers, Hayit Greenspan, Bram van Ginneken, 2016 .

Color- and Texture-based Image Segmentation Using the Expectation-Maximization Algorithm and its Application to Content-Based Image Retrieval.

Hayit Greenspan, Serge J. Belongie, Serge Belongie, 1998, ICCV 1998.

Color- and texture-based image segmentation using EM and its application to content-based image retrieval

Jitendra Malik, Hayit Greenspan, Serge J. Belongie, 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).

Synthetic data augmentation using GAN for improved liver lesion classification

Hayit Greenspan, Jacob Goldberger, Maayan Frid-Adar, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Automated and Interactive Lesion Detection and Segmentation in Uterine Cervix Images

Hayit Greenspan, Jacob Goldberger, Amir Alush, 2010, IEEE Transactions on Medical Imaging.

The Liver Tumor Segmentation Benchmark (LiTS) pdf

Hao Chen, Leo Joskowicz, Alexandre Hostettler, 2019, Medical Image Anal..

Recognition of Images in Large Databases Using a Learning Framework

Jitendra Malik, Hayit Greenspan, Serge J. Belongie, 1997 .

Constrained Gaussian mixture model framework for automatic segmentation of MR brain images

Hayit Greenspan, Jacob Goldberger, Amit Ruf, 2006, IEEE Transactions on Medical Imaging.

Task-Driven Dictionary Learning Based on Mutual Information for Medical Image Classification

Hayit Greenspan, Jacob Goldberger, Eli Konen, 2017, IEEE Transactions on Biomedical Engineering.

Convolutional Neural Networks for Radiologic Images: A Radiologist's Guide.

H. Greenspan, E. Klang, M. Amitai, 2019, Radiology.

A Probabilistic Framework for Spatio-Temporal Video Representation & Indexing

Hayit Greenspan, Jacob Goldberger, Arnaldo Mayer, 2002, ECCV.

Applying the information bottleneck principle to unsupervised clustering of discrete and continuous image representations

Shiri Gordon, Hayit Greenspan, Jacob Goldberger, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

CT Image-based Decision Support System for Categorization of Liver Metastases Into Primary Cancer Sites: Initial Results.

H. Greenspan, I. Diamant, E. Klang, 2017, Academic radiology.

Learning Probabilistic Fusion of Multilabel Lesion Contours

Hayit Greenspan, Jacob Goldberger, Gal Cohen, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Bone Structures Extraction and Enhancement in Chest Radiographs via CNN Trained on Synthetic Data

Hayit Greenspan, Ophir Gozes, H. Greenspan, 2020, 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI).

Video Representation via a Continuous Probabilistic Framework

H. Greenspan, J. Goldberger, Arnaldo Mayer, 2007 .

Quantitative phase microscopy spatial signatures of cancer cells

H. Greenspan, N. Shaked, Darina Roitshtain, 2017, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

Improving Liver Lesion Detection using CT-to-PET FCN and GAN Networks

H. Greenspan, M. Amitai, S. Ben-Haim, 2018 .

Automated Tissue Classification of noisy MR Images of the Brain Using Constrained Multiple Multivariate Gaussian Mixture Model ( CGMM )

H. Greenspan, A. Ruf, 2005 .

Invariant Texture Recognition Using a Steerable Pyramid

Serge J. Belongie, P. Perona, H. Greenspan, 1994 .

Modeling the Intra-class Variability for Liver Lesion Detection Using a Multi-class Patch-Based CNN

Hayit Greenspan, Jacob Goldberger, Maayan Frid-Adar, 2017, Patch-MI@MICCAI.

A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises pdf

Ronald M. Summers, Jerry L. Prince, Daniel Rueckert, 2020, Proceedings of the IEEE.

Weakly supervised brain tumor segmentation via semantic affinity deep neural network

H. Greenspan, Moshe Yerachmiel, 2022, Medical Imaging.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support

Jaime S. Cardoso, M. Jorge Cardoso, H. Greenspan, 2017, Lecture Notes in Computer Science.

Classification of lymphoproliferative disorders by spectral imaging of the nucleus.

H. Greenspan, C. Rothmann, Z. Malik, 2002, Histology and histopathology.

Glass pattern recognition with neural-networks

Yehoshua Y. Zeevi, Hayit Greenspan, Moshe Porat, 1988, Neural Networks.

Deep Learning in Medical Applications

Hayit Greenspan, H. Greenspan, 2016, BIODEVICES.

Enhancing Images By Nonlinear Extrapolation In Frequency

Hayit Greenspan, Charles H. Anderson, H. Greenspan, 1995 .

Quantification of Intra-Muscular Adipose Infiltration in Calf/Thigh MRI Using Fully and Weakly Supervised Semantic Segmentation

H. Greenspan, N. Ben-Eliezer, D. Bendahan, 2022, Bioengineering.

Involvement of IKAP in Peripheral Target Innervation and in Specific JNK and NGF Signaling in Developing PNS Neurons

H. Greenspan, M. Weil, A. Abashidze, 2014, PloS one.

Deep learning based multiple sclerosis lesion detection utilizing synthetic data generation and soft attention mechanism

H. Greenspan, N. Ben-Eliezer, Omer Shmueli, 2022, Medical Imaging.

Weakly Supervised Multimodal 30-Day All-Cause Mortality Prediction for Pulmonary Embolism Patients

H. Greenspan, E. Klang, E. Konen, 2022, 2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI).

RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning

H. Greenspan, Z. Fayad, P. Robson, 2022, Radiology. Artificial intelligence.

Fully automated prediction of liver fibrosis using deep learning analysis of gadoxetic acid–enhanced MRI

H. Greenspan, S. Friedman, B. Taouli, 2020, European Radiology.

A Self Supervised StyleGAN for Image Annotation and Classification With Extremely Limited Labels

H. Greenspan, R. Giryes, Dana Cohen Hochberg, 2022, IEEE Transactions on Medical Imaging.

HeartBEiT: Vision Transformer for Electrocardiogram Data Improves Diagnostic Performance at Low Sample Sizes

Benjamin S. Glicksberg, Department of Preventive Medicine, H. Greenspan, 2022, ArXiv.

Super-Resolution in Medical Imaging

Hayit Greenspan, H. Greenspan, 2009, Comput. J..

Super-resolution in MRI

Hayit Greenspan, Nahum Kiryati, Sharon Peled, 2002, Proceedings IEEE International Symposium on Biomedical Imaging.

MRI Inter-slice Reconstruction Using Super-Resolution

Hayit Greenspan, Nahum Kiryati, Sharon Peled, 2001, MICCAI.

Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis

Peter A. Calabresi, Snehashis Roy, Aaron Carass, 2020, Scientific Reports.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: 4th International Workshop, DLMIA 2018, and 8th International Workshop, ML-CDS 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 20, 2018, Proceedings

Gustavo Carneiro, João Paulo Papa, Lena Maier-Hein, 2018, DLMIA/ML-CDS@MICCAI.

Learning Rotation Invariant Features For Cryogenic Electron Microscopy Image Reconstruction pdf

Hayit Greenspan, Koby Bibas, Gili Weiss-Dicker, 2021, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

A Soft STAPLE Algorithm Combined with Anatomical Knowledge

Hayit Greenspan, Jacob Goldberger, Eytan Kats, 2019, MICCAI.

Biomedical Imaging Informatics

Hayit Greenspan, Daniel L. Rubin, James F. Brinkley, 2021, Biomedical Informatics.

Image enhancement by nonlinear extrapolation in frequency space

Hayit Greenspan, Charles H. Anderson, H. Greenspan, 1994, Electronic Imaging.

COVID-19 in CXR: From Detection and Severity Scoring to Patient Disease Monitoring pdf

Rula Amer, Jannette Nassar, Maayan Frid-Adar, 2020, IEEE Journal of Biomedical and Health Informatics.

COVID-19 opacity segmentation in chest CT via HydraNet: a joint learning multi-decoder network

Hayit Greenspan, Nimrod Sagie, Shiri Almog, 2021, Medical Imaging.

Transfer Learning with a Layer Dependent Regularization for Medical Image Segmentation

Hayit Greenspan, Jacob Goldberger, Nimrod Sagie, 2021, MLMI@MICCAI.

Rapid AI Development Cycle for the Coronavirus (COVID-19) Pandemic: Initial Results for Automated Detection & Patient Monitoring using Deep Learning CT Image Analysis pdf

Hayit Greenspan, Maayan Frid-Adar, Ophir Gozes, 2020, ArXiv.

Chest pathology identification using deep feature selection with non-medical training

Hayit Greenspan, Lior Wolf, Eli Konen, 2018, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Multiple Sclerosis Lesion Detection Using Constrained GMM and Curve Evolution

Hayit Greenspan, Jacob Goldberger, Oren Freifeld, 2009, Int. J. Biomed. Imaging.

Weakly Supervised Attention Model for RV StrainClassification from volumetric CTPA Scans pdf

Hayit Greenspan, Edith M. Marom, Eli Konen, 2021, Comput. Methods Programs Biomed..

RV strain classification from 3D CTPA scans using weakly supervised residual attention model

Hayit Greenspan, Edith M. Marom, Eli Konen, 2021, Medical Imaging.

Statistical Imaging for Modeling and Identification of Bacterial Types

Hayit Greenspan, Shimon Abboud, Sigal Trattner, 2004, ECCV Workshops CVAMIA and MMBIA.

Automatic identification of bacterial types using statistical imaging methods

Hayit Greenspan, Shimon Abboud, Sigal Trattner, 2003, IEEE Transactions on Medical Imaging.

Position paper on COVID-19 imaging and AI: From the clinical needs and technological challenges to initial AI solutions at the lab and national level towards a new era for AI in healthcare

Wiro J. Niessen, Raúl San José Estépar, Mads Nielsen, 2020, Medical Image Analysis.

Automated supervised segmentation of anatomical fiber tracts using an AdaBoost framework

Hayit Greenspan, Rula Amer, Guy Alexandroni, 2016, 2016 IEEE International Conference on the Science of Electrical Engineering (ICSEE).

Co-registration of White Matter Tractographies by Adaptive-Mean-Shift and Gaussian Mixture Modeling

Hayit Greenspan, Arnaldo Mayer, Shmuel Miron, 2010, IEEE Transactions on Medical Imaging.

A Review of Deep Learning in Medical Imaging: Imaging Traits, Technology Trends, Case Studies With Progress Highlights, and Future Promises

Jerry L Prince, H. Greenspan, J. Duncan, 2020, Proceedings of the IEEE.

Endotracheal Tube Detection and Segmentation in Chest Radiographs using Synthetic Data pdf

Hayit Greenspan, Rula Amer, Maayan Frid-Adar, 2019, MICCAI.

A Sparsely Distributed Intra-cardial Ultrasonic Array for Real-Time Endocardial Mapping

Hayit Greenspan, Alon Baram, Zvi Freidman, 2019, MICCAI.

Non-Parametric Texture Learning

Hayit Greenspan, H. Greenspan, 1996 .

Piecewise smooth affine registration of point-sets with application to DT-MRI brain fiber-data

Hayit Greenspan, Arnaldo Mayer, Nir A. Sochen, 2010, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Classification trees for fast segmentation of DTI brain fiber tracts

Hayit Greenspan, Arnaldo Mayer, Gali Zimmerman-Moreno, 2008, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.

Bundles of interest based registration of White Matter tractographies

Hayit Greenspan, Arnaldo Mayer, H. Greenspan, 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Adaptive mean-shift registration of white matter tractographies

Hayit Greenspan, Arnaldo Mayer, Orly Zvitia, 2008, 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

White matter tractographies registration using Gaussian mixture modeling

Hayit Greenspan, Arnaldo Mayer, Orly Zvitia, 2008, SPIE Medical Imaging.

Direct Registration of White Matter Tractographies with Application to Atlas Construction

Hayit Greenspan, Arnaldo Mayer, H. Greenspan, 2007 .

Cross-Modality Synthesis from CT to PET using FCN and GAN Networks for Improved Automated Lesion Detection pdf

Hayit Greenspan, Eli Konen, Avi Ben-Cohen, 2018, Eng. Appl. Artif. Intell..

Evaluation of center-line extraction algorithms in quantitative coronary angiography

Shmuel Einav, Hayit Greenspan, Ofer Barnea, 2001, IEEE Transactions on Medical Imaging.

Automatic detection of cell divisions (mitosis) in live-imaging microscopy images using Convolutional Neural Networks

Hayit Greenspan, Amit Gefen, Dafna Benayahu, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Fully Convolutional Network for Liver Segmentation and Lesions Detection

Hayit Greenspan, Michal Amitai, Idit Diamant, 2016, LABELS/DLMIA@MICCAI.

Chest pathology detection using deep learning with non-medical training

Hayit Greenspan, Lior Wolf, Eli Konen, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Automatic liver volume segmentation and fibrosis classification

Hayit Greenspan, Evgeny Bal, Eyal Klang, 2018, Medical Imaging.

Automated analysis of individual sperm cells using stain‐free interferometric phase microscopy and machine learning

Hayit Greenspan, Natan T Shaked, Simcha K. Mirsky, 2017, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

Semi-supervised lung nodule retrieval pdf

Hayit Greenspan, Mark Loyman, H. Greenspan, 2020, ArXiv.

Lung nodule retrieval using semantic similarity estimates

Hayit Greenspan, Mark Loyman, H. Greenspan, 2019, Medical Imaging.

Evaluation of uterine cervix segmentations using ground truth from multiple experts

Shelly Lotenberg, Shiri Gordon, Hayit Greenspan, 2009, Comput. Medical Imaging Graph..

Automatic evaluation of uterine cervix segmentations

Shelly Lotenberg, Shiri Gordon, Rodney Long, 2007, SPIE Medical Imaging.

Electrostatic Selectivity of Volatile Organic Compounds Using Electrostatically Formed Nanowire Sensor.

H. Greenspan, Avi Ben-Cohen, Y. Rosenwaks, 2018, ACS sensors.

Content-Based Image Retrieval in Radiology: Current Status and Future Directions

Hayit Greenspan, Daniel L. Rubin, Burak Acar, 2010, Journal of Digital Imaging.

Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset

Hayit Greenspan, Ophir Gozes, H. Greenspan, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

An Adversarial Learning Approach to Medical Image Synthesis for Lesion Detection

Hayit Greenspan, Liyan Sun, Jiexiang Wang, 2018, IEEE Journal of Biomedical and Health Informatics.

Can Born Approximate the Unborn? A New Validity Criterion for the Born Approximation in Microscopic Imaging

Hayit Greenspan, Nir A. Sochen, Micha Feigin, 2007, 2007 IEEE 11th International Conference on Computer Vision.

Improved Patch-Based Automated Liver Lesion Classification by Separate Analysis of the Interior and Boundary Regions

Hayit Greenspan, Daniel L. Rubin, Assaf Hoogi, 2016, IEEE Journal of Biomedical and Health Informatics.

Multi-phase liver lesions classification using relevant visual words based on mutual information

Hayit Greenspan, Jacob Goldberger, Eyal Klang, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

Integration of Chest CT CAD into the Clinical Workflow and Impact on Radiologist Efficiency.

Hayit Greenspan, Fereidoun Abtin, Irene da Costa, 2019, Academic radiology.

Evaluating White Matter Lesion Segmentations with Refined Sørensen-Dice Analysis

William R. Gray Roncal, Jerry L Prince, Jacob C. Reinhold, 2020, Scientific Reports.

A multi-view deep learning architecture for classification of breast microcalcifications

Hayit Greenspan, Jacob Goldberger, Alan Joseph Bekker, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

Medical Image Categorization and Retrieval for PACS Using the GMM-KL Framework

Hayit Greenspan, Adi Pinhas, H. Greenspan, 2007, IEEE Transactions on Information Technology in Biomedicine.

Combined Neural Network and Rule-Based Framework for Probabilistic Pattern Recognition and Discovery

Rama Chellappa, Hayit Greenspan, Rodney M. Goodman, 1991, NIPS.

Multimodal fusion models for pulmonary embolism mortality prediction

H. Greenspan, E. Klang, E. Konen, 2023, Scientific reports.

Training a neural network based on unreliable human annotation of medical images

Hayit Greenspan, Jacob Goldberger, Yair Dgani, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Improving CNN Training using Disentanglement for Liver Lesion Classification in CT

Hayit Greenspan, Roey Mechrez, Avi Ben-Cohen, 2018, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Lung Structures Enhancement in Chest Radiographs via CT Based FCNN Training

Hayit Greenspan, Ophir Gozes, H. Greenspan, 2018, RAMBO+BIA+TIA@MICCAI.

Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Results pdf

Hayit Greenspan, Michal Amitai, Avi Ben-Cohen, 2017, SASHIMI@MICCAI.

An efficient image similarity measure based on approximations of KL-divergence between two gaussian mixtures

Shiri Gordon, Hayit Greenspan, Jacob Goldberger, 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

Multi-view longitudinal CNN for multiple sclerosis lesion segmentation

Hayit Greenspan, Ariel Birenbaum, H. Greenspan, 2017, Eng. Appl. Artif. Intell..

RadImageNet: A Large-scale Radiologic Dataset for Enhancing Deep Learning Transfer Learning Research

Ying Wang, Hayit Greenspan, Timothy Deyer, 2021 .

Coronavirus Detection and Analysis on Chest CT with Deep Learning pdf

Hayit Greenspan, Maayan Frid-Adar, Ophir Gozes, 2020, ArXiv.

Deep learning with non-medical training used for chest pathology identification

Hayit Greenspan, Lior Wolf, Yaniv Bar, 2015, Medical Imaging.

Texture feature based liver lesion classification

Hayit Greenspan, Idit Diamant, Yeela Doron, 2014, Medical Imaging.

Quantifying the margin sharpness of lesions on radiological images for content-based image retrieval.

Hayit Greenspan, Sandy Napel, Daniel Rubin, 2012, Medical physics.

LESION DETECTION IN NOISY MR BRAIN IMAGES USING CONSTRAINED GMM AND ACTIVE CONTOURS

Hayit Greenspan, Jacob Goldberger, Oren Freifeld, 2007, 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

The fiber-density-coreset for redundancy reduction in huge fiber-sets

Hayit Greenspan, Gali Zimmerman-Moreno, Nir A. Sochen, 2017, NeuroImage.

White Matter Fiber Set Simplification by Redundancy Reduction with Minimum Anatomical Information Loss

Hayit Greenspan, Gali Zimmerman Moreno, Guy Alexandroni, 2016 .

Context-based image modelling

Hayit Greenspan, Yossi Rubner, Guy Dvir, 2002, Object recognition supported by user interaction for service robots.

Context-dependent segmentation and matching in image databases

Hayit Greenspan, Yossi Rubner, Guy Dvir, 2004, Comput. Vis. Image Underst..

Automated temporal tracking and segmentation of lymphoma on serial CT examinations.

Hayit Greenspan, Daniel L Rubin, Sandy Napel, 2011, Medical physics.

A mixture of views network with applications to multi-view medical imaging

Hayit Greenspan, Jacob Goldberger, Yaniv Shachor, 2020, Neurocomputing.

Longitudinal Multiple Sclerosis Lesion Segmentation Using Multi-view Convolutional Neural Networks

Hayit Greenspan, Ariel Birenbaum, H. Greenspan, 2016, LABELS/DLMIA@MICCAI.

Patch-Based Segmentation with Spatial Consistency: Application to MS Lesions in Brain MRI

Hayit Greenspan, Jacob Goldberger, Roey Mechrez, 2016, Int. J. Biomed. Imaging.

Fully convolutional network and sparsity-based dictionary learning for liver lesion detection in CT examinations

Hayit Greenspan, Eli Konen, Eyal Klang, 2018, Neurocomputing.

Multi-View Probabilistic Classification of Breast Microcalcifications

Hayit Greenspan, Jacob Goldberger, Alan Joseph Bekker, 2016, IEEE Transactions on Medical Imaging.

Probabilistic Spatial-Temporal Segmentation of Multiple Sclerosis Lesions

Hayit Greenspan, Allon Shahar, H. Greenspan, 2004, ECCV Workshops CVAMIA and MMBIA.

X-ray Categorization and Retrieval on the Organ and Pathology Level, Using Patch-Based Visual Words

Hayit Greenspan, Jacob Goldberger, Eli Konen, 2011, IEEE Transactions on Medical Imaging.

A Machine Learning Approach to the Interpretation of Cardiopulmonary Exercise Tests: Development and Validation

H. Greenspan, O. Inbar, M. Scheinowitz, 2021, Pulmonary medicine.

Projection-Based Approach to Image Analysis: Pattern Recognition and Representation in the Position-Orientation Space

H. Greenspan, M. Porat, Y.Y. Zeevi, 1992, IEEE Trans. Pattern Anal. Mach. Intell..

Tissue Classification of Noisy MR Brain Images Using Constrained GMM

Hayit Greenspan, Jacob Goldberger, Amit Ruf, 2005, MICCAI.

White Matter Fiber Representation Using Continuous Dictionary Learning

Hayit Greenspan, Alexander M. Bronstein, Raja Giryes, 2017, MICCAI.

Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks

H. Greenspan, Jean-Baptiste Schiratti, S. Jégou, 2023, European Radiology.

Automatic Segmentation of Muscle Tissue and Inter-muscular Fat in Thigh and Calf MRI Images pdf

Hayit Greenspan, David Bendahan, Rula Amer, 2019, MICCAI.

Joint Liver Lesion Segmentation and Classification via Transfer Learning pdf

Hayit Greenspan, Michal Heker, H. Greenspan, 2020, ArXiv.

Hierarchical Fine-Tuning for joint Liver Lesion Segmentation and Lesion Classification in CT

Hayit Greenspan, Avi Ben-Cohen, Michal Heker, 2019, 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Estimation of subvoxel fat infiltration in neurodegenerative muscle disorders using quantitative multi‐T2 analysis

H. Greenspan, T. Blumenfeld‐Katzir, Y. le Fur, 2023, NMR in biomedicine.

Anne L. Martel, Marc Combalia, Veronica Vilaplana, 2018, DLMIA/ML-CDS@MICCAI.

Automated method for detection and segmentation of liver metastatic lesions in follow-up CT examinations

Hayit Greenspan, Eyal Klang, Idit Diamant, 2015, Journal of medical imaging.

Shape Priors for Segmentation of the Cervix Region Within Uterine Cervix Images

Shelly Lotenberg, Shiri Gordon, Hayit Greenspan, 2008, SPIE Medical Imaging.

Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support pdf

Jaime S. Cardoso, Mitko Veta, Josien P. W. Pluim, 2017, Lecture Notes in Computer Science.

Soft Labeling by Distilling Anatomical Knowledge for Improved MS Lesion Segmentation

Hayit Greenspan, Jacob Goldberger, Eytan Kats, 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

Cancer-Cell Deep-Learning Classification by Integrating Quantitative-Phase Spatial and Temporal Fluctuations

H. Greenspan, N. Shaked, A. Baram, 2021, Cells.

Probabilistic space-time video modeling via piecewise GMM

Hayit Greenspan, Jacob Goldberger, Arnaldo Mayer, 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

An Adaptive Mean-Shift Framework for MRI Brain Segmentation

Hayit Greenspan, Arnaldo Mayer, H. Greenspan, 2009, IEEE Transactions on Medical Imaging.

Mixture model for face-color modeling and segmentation

Hayit Greenspan, Jacob Goldberger, Itay Eshet, 2001, Pattern Recognit. Lett..

Lung texture classification using bag of visual words

Hayit Greenspan, Idit Diamant, Marina Asherov, 2014, Medical Imaging.

Automatic Detection of Anatomical Landmarks in Uterine Cervix Images

Shelly Lotenberg, Shiri Gordon, Hayit Greenspan, 2009, IEEE Transactions on Medical Imaging.

Automatic landmark detection in uterine cervix images for indexing in a content-retrieval system

Shiri Gordon, Hayit Greenspan, Gali Zimmerman-Moreno, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Combining Region and Edge Cues for Image Segmentation in a Probabilistic Gaussian Mixture Framework

Hayit Greenspan, Jacob Goldberger, Omer Rotem, 2009, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

A probabilistic framework for the spatio-temporal segmentation of multiple sclerosis lesions in MR images of the brain

Hayit Greenspan, Arnaldo Mayer, Allon Shahar, 2003, SPIE Medical Imaging.

Psychophysical Evaluation of Visual vs. Computer‐Aided Detection of Brain Lesions on Magnetic Resonance Images

H. Greenspan, T. Blumenfeld‐Katzir, N. Ben-Eliezer, 2022, Journal of magnetic resonance imaging : JMRI.

Breast tissue classification in mammograms using visual words

H. Greenspan, I. Diamant, J. Goldberger, 2012, 2012 IEEE 27th Convention of Electrical and Electronics Engineers in Israel.

Chest x-ray characterization: from organ identification to pathology categorization

Hayit Greenspan, Jacob Goldberger, Eli Konen, 2010, MIR '10.

Quantitative prediction of right ventricular and size and function from the electrocardiogram

H. Greenspan, R. Do, B. Gelb, 2023, medRxiv.

AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer-aided diagnosis in medical imaging.

Lubomir M. Hadjiiski, Ravi K. Samala, Kenny H. Cha, 2022, Medical Physics (Lancaster).

Regularized super-resolution of brain MRI

Hayit Greenspan, Yossi Rubner, Avraham Ben-Ezra, 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

Improved CSF classification and lesion detection in MR brain images with multiple sclerosis

Hayit Greenspan, Yulian Wolff, Shmuel Miron, 2007, SPIE Medical Imaging.

Segmentation of brain MRI by adaptive mean shift

Hayit Greenspan, Arnaldo Mayer, H. Greenspan, 2006, 3rd IEEE International Symposium on Biomedical Imaging: Nano to Macro, 2006..

Parametric and Non-Parametric Clustering for Segmentation

Hayit Greenspan, Tanveer Syeda-Mahmood, H. Greenspan, 2010 .

Nodule2vec: a 3D Deep Learning System for Pulmonary Nodule Retrieval Using Semantic Representation pdf

Hayit Greenspan, Ilia Kravets, Tal Heletz, 2020, MICCAI.

Context-based segmentation of image sequences

Hayit Greenspan, Jacob Goldberger, H. Greenspan, 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Supervised Domain Adaptation by transferring both the parameter set and its gradient

H. Greenspan, Shaya Goodman, Jacob Goldberger, 2023, Neurocomputing.

Visualizing and enhancing a deep learning framework using patients age and gender for chest x-ray image retrieval

Hayit Greenspan, Yaron Anavi, Ilya Kogan, 2016, SPIE Medical Imaging.

Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique

H. Greenspan, B. Ginneken, Ronald M. Summers, 2016, IEEE Trans. Medical Imaging.

A comparative study for chest radiograph image retrieval using binary texture and deep learning classification

Hayit Greenspan, Yaron Anavi, Ilya Kogan, 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

A foundational vision transformer improves diagnostic performance for electrocardiograms

Benjamin S. Glicksberg, H. Greenspan, E. Argulian, 2023, NPJ digital medicine.

Unsupervised image-set clustering using an information theoretic framework

H. Greenspan, J. Goldberger, S. Gordon, 2006, IEEE Transactions on Image Processing.

Improving the Segmentation of Anatomical Structures in Chest Radiographs Using U-Net with an ImageNet Pre-trained Encoder

Hayit Greenspan, Rula Amer, Maayan Frid-Adar, 2018, RAMBO+BIA+TIA@MICCAI.

Automated Triage Of Covid-19 From Various Lung Abnormalities Using Chest Ct Features pdf

Jannette Nassar, Maayan Frid-Adar, Hayit Greenspan, 2020, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

TAU MIPLAB at ImageClef 2008

Hayit Greenspan, Jacob Goldberger, Uri Avni, 2008, CLEF.

AALIM: A Cardiac Clinical Decision Support System Powered By Advanced Multi-modal Analytics

Hayit Greenspan, Kilian M. Pohl, David Beymer, 2010, MedInfo.

Keyword spotting for cursive document retrieval

Rodney M. Goodman, P. Keaton, Hayit Greenspan, 1997, Proceedings Workshop on Document Image Analysis (DIA'97).

Automated retrieval of CT images of liver lesions on the basis of image similarity: method and preliminary results.

H. Greenspan, D. Rubin, S. Napel, 2010, Radiology.

PLPP: A Pseudo Labeling Post-Processing Strategy for Unsupervised Domain Adaptation

H. Greenspan, Jacob Goldberger, Tomer Bar Natan, 2023, 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI).

Quantitative Prediction of Right Ventricular Size and Function From the ECG

H. Greenspan, B. Gelb, A. Vaid, 2023, Journal of the American Heart Association.

Learning to combine decisions from multiple mammography views

Hayit Greenspan, Jacob Goldberger, Alan Joseph Bekker, 2015, 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI).

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

H. Greenspan, Z. Fayad, X. Mei, 2024, NMR in biomedicine.

Deep Learning for Medical Image Analysis

H. Greenspan, C. Meinel, Haojin Yang, 2017 .

Detecting Anatomy Openings in the Left Atrium Via a Triangular Ultrasonic Array Using Deep Learning

H. Greenspan, O. Ovadia, A. Baram, 2023, 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI).