An Integrated Segmentation and Classification Approach Applied to Multiple Sclerosis Analysis. - Ayelet Akselrod-Ballin; Meirav Galun; Ronen Basri; Achi Brandt; Moshe John Gomori; Massimo Filippi; Paola Valsasina (CVPR (1), 2006)

Atlas Guided Identification of Brain Structures by Combining 3D Segmentation and SVM Classification. - Ayelet Akselrod-Ballin; Meirav Galun; Moshe John Gomori; Ronen Basri; Achi Brandt (MICCAI (2), 2006)

Prior Knowledge Driven Multiscale Segmentation of Brain MRI. - Ayelet Akselrod-Ballin; Meirav Galun; Moshe John Gomori; Achi Brandt; Ronen Basri (MICCAI (2), 2007)

Distinctive and compact features. - Ayelet Akselrod-Ballin; Shimon Ullman (Image Vis. Comput., 2008)

Improved Registration for Large Electron Microscopy Images. - Ayelet Akselrod-Ballin; Davi Bock; R. Clay Reid; Simon K. Warfield (ISBI, 2009)

Accelerating Feature Based Registration Using the Johnson-Lindenstrauss Lemma. - Ayelet Akselrod-Ballin; Davi Bock; R. Clay Reid; Simon K. Warfield (MICCAI (1), 2009)

Automatic Segmentation and Classification of Multiple Sclerosis in Multichannel MRI. - Ayelet Akselrod-Ballin; Meirav Galun; Moshe John Gomori; Massimo Filippi; Paola Valsasina; Ronen Basri; Achi Brandt (IEEE Trans. Biomed. Eng., 2009)

Accelerating Image Registration With the Johnson-Lindenstrauss Lemma: Application to Imaging 3-D Neural Ultrastructure With Electron Microscopy. - Ayelet Akselrod-Ballin; Davi Bock; R. Clay Reid; Simon K. Warfield (IEEE Trans. Medical Imaging, 2011)

Sequence alignment of in-utero fetal tissue MRI in mice. - Ayelet Akselrod-Ballin; Reut Avni; Michal Neeman (ISBI, 2014)

A Region Based Convolutional Network for Tumor Detection and Classification in Breast Mammography. - Ayelet Akselrod-Ballin; Leonid Karlinsky; Sharon Alpert; Sharbell Y. Hasoul; Rami Ben-Ari; Ella Barkan (LABELS/DLMIA@MICCAI, 2016)

Domain specific convolutional neural nets for detection of architectural distortion in mammograms. - Rami Ben-Ari; Ayelet Akselrod-Ballin; Leonid Karlinsky; Sharbell Y. Hashoul (ISBI, 2017)

Deep Learning for Automatic Detection of Abnormal Findings in Breast Mammography. - Ayelet Akselrod-Ballin; Leonid Karlinsky; Alon Hazan; Ran Bakalo; Ami Ben Horesh; Yoel Shoshan; Ella Barkan (DLMIA/ML-CDS@MICCAI, 2017)

Mammogram Classification and Abnormality Detection from Nonlocal Labels using Deep Multiple Instance Neural Network. - Yoni Choukroun; Ran Bakalo; Rami Ben-Ari; Ayelet Akselrod-Ballin; Ella Barkan; Pavel Kisilev (VCBM, 2017)

Siamese Network for Dual-View Mammography Mass Matching. - Shaked Perek; Alon Hazan; Ella Barkan; Ayelet Akselrod-Ballin (RAMBO+BIA+TIA@MICCAI, 2018)

Mammography Dual View Mass Correspondence. - Shaked Perek; Alon Hazan; Ella Barkan; Ayelet Akselrod-Ballin (CoRR, 2018)

A CNN based method for automatic mass detection and classification in mammograms. - Ayelet Akselrod-Ballin; Leonid Karlinsky; Sharon Alpert; Sharbell Y. Hasoul; Rami Ben-Ari; Ella Barkan (Comput. methods Biomech. Biomed. Eng. Imaging Vis., 2019)

3D Convolutional Sequence to Sequence Model for Vertebral Compression Fractures Identification in CT. - David Chettrit; Tomer Meir; Hila Lebel; Mila Orlovsky; Ronen Gordon; Ayelet Akselrod-Ballin; Amir Bar (MICCAI (6), 2020)

The Case of Missed Cancers: Applying AI as a Radiologist's Safety Net. - Michal Chorev; Yoel Shoshan; Ayelet Akselrod-Ballin; Adam Spiro; Shaked Naor; Alon Hazan; Vesna Resende Barros; Iuliana Weinstein; Esma Herzel; Varda Shalev; Michal Guindy; Michal Rosen-Zvi (MICCAI (6), 2020)

Learning Interclass Relations for Image Classification. - Raouf Muhamedrahimov; Amir Bar; Ayelet Akselrod-Ballin (CoRR, 2020)

Learning Interclass Relations for Intravenous Contrast Phase Classification in CT. - Raouf Muhamedrahimov; Amir Bar; Ayelet Akselrod-Ballin (MIDL, 2021)

Leveraging Comprehensive Health Records for Breast Cancer Risk Prediction: A Binational Assessment. - Michal Chorev; Vesna Resende Barros; Adam Spiro; Ella Evron; Ella Barkan; Oren Kagan; Mika Amit; Michal Ozery-Flato; Ayelet Akselrod-Ballin; Varda Shalev; Michal Rosen-Zvi; Michal Guindy (AMIA, 2022)

Using Machine Learning to Identify Intravenous Contrast Phases on Computed Tomography. - Raouf Muhamedrahimov; Amir Bar; Jonathan Laserson; Ayelet Akselrod-Ballin; Eldad Elnekave (Comput. Methods Programs Biomed., 2022)

Deep active learning framework for chest-abdominal CT scans segmentation. - Lital Rokach; Yehudit Aperstein; Ayelet Akselrod-Ballin (Expert Syst. Appl., 2025)