Dr. Anaby is the head of The Breast Cancer Imaging Laboratory at the Diagnostic Imaging Department, specializing in MRI, Computer Vision and artificial intelligence.
Education
2015-2017 Postdoctoral, Cardiff University, Wales
Supervised by Prof. Derek Jones
2010-2015 PhD, Chemistry, Tel Aviv University, Tel Aviv, Israel.
Supervised by Prof. Yoram Cohen
2007-2009 MSc, Chemistry, Tel Aviv University. Tel Aviv, Israel
Supervised by Prof. Yoram Cohen
1999-2004 BA, Molecular Biochemistry, Technion, Haifa, Israel
1999-2004 BSc, Biochemical Engineering, Technion, Haifa, Israel
Affiliations
Division of Diagnostics Imaging, Sheba Medical Center, Tel Hashomer, Israel
Research Interests
The Breast Cancer Imaging Lab focuses on MRI-based breast cancer diagnosis and screening, aiming to achieve an earlier detection, personalize the screening pathway in high-risk women and shorten radiology reading times. Work is based on image processing and artificial intelligence, utilizing hundreds of MRI scans that are available at the Meirav Breast Center, many of which include biopsy-proven lesions. We utilize both conventional MRI and advanced ultrafast acquisitions. Deep learning models are used for segmentation, detection and classification of breast lesions, particularly sub-centimeter lesions, which may be more difficult to detect and characterize radiologically. Imaging features are also combined with clinical and demographic data aiming to achieve higher accuracy. Additionally, we are interested in predicting treatment response and identifying suspicious lymph nodes in the breasts and axillae.
Publications
Here is a link to the publications of Dr. Anaby in Pubmed.
Research Grants & Awards
2020, Co-PI, Evaluation of artificial intelligence for personalized risk assessment in BRCA carriers. Israel Cancer Association.
2021, PI, An ‘Earlier than Early’ detection of breast cancer in BRCA carriers based on radiomics and AI methods applied on DCE MRI. 'Earlier.org'
2021, PI, An ‘Earlier than Early’ diagnosis of soon-to-develop breast cancer in BRCA carriers – personalized risk assessment using MRI and artificial intelligence. The 'Dahlia Greidinger Cancer Fund'.
2022, Co-PI, Brilliant study: Breast MRI-based artificial intelligence to identify high risk areas in residual breast tissue after mastectomy and reconstruction. ASCO + ICRF.
2024, PI, Classification of overlooked or misinterpreted sub-centimeter breast lesions by Ultrafast MRI. Israel Cancer Association.
2024, PI, Transforming breast cancer diagnosis: A novel approach for diagnostic precision. ICRF.
2024, PI, Artificial intelligence (AI) for enhancing the diagnostic capability of breast MRI: advanced tool for clinical use. 'Ezvonot'.
2023, TELEM Excellence Research Program, Sheba Medical Center
