PD-DWI: Predicting Response to Neoadjuvant Chemotherapy in Invasive Breast Cancer with Physiologically-Decomposed Diffusion-Weighted MRI Machine-Learning Model.

Maya Gilad; Moti Freiman

doi:https://doi.org/10.1007/978-3-031-16437-8_4

PD-DWI: Predicting Response to Neoadjuvant Chemotherapy in Invasive Breast Cancer with Physiologically-Decomposed Diffusion-Weighted MRI Machine-Learning Model.

Maya Gilad, Moti Freiman

Biomedical Engineering

Technion - Israel Institute of Technology

Research output: Contribution to conference › Paper › peer-review

Original language	Undefined/Unknown
Pages	36-45
DOIs	https://doi.org/10.1007/978-3-031-16437-8_4
State	Published - 2022

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Access to Document

https://doi.org/10.1007/978-3-031-16437-8_4

https://dblp.org/rec/conf/miccai/GiladF22

Cite this

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title = "PD-DWI: Predicting Response to Neoadjuvant Chemotherapy in Invasive Breast Cancer with Physiologically-Decomposed Diffusion-Weighted MRI Machine-Learning Model.",

author = "Maya Gilad and Moti Freiman",

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AU - Gilad, Maya

AU - Freiman, Moti

N1 - DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

PY - 2022

Y1 - 2022

U2 - https://doi.org/10.1007/978-3-031-16437-8_4

DO - https://doi.org/10.1007/978-3-031-16437-8_4

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SP - 36

EP - 45

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