A sparse deep learning approach for automatic segmentation of human vasculature in multispectral optoacoustic tomography-Reference-Cited by-同舟云学术

A sparse deep learning approach for automatic segmentation of human vasculature in multispectral optoacoustic tomography

Published:2020-12 Issue: Volume:20 Page:100203
ISSN:2213-5979
Container-title:Photoacoustics
language:en
Short-container-title:Photoacoustics

Author:

Chlis Nikolaos-Kosmas,Karlas Angelos,Fasoula Nikolina-Alexia,Kallmayer Michael,Eckstein Hans-Henning,Theis Fabian J.,Ntziachristos Vasilis,Marr Carsten

Funder

Graduate School of Quantitative Biosciences Munich

Graduate School QBM, by the Helmholtz Association

BMBF

Chan Zuckerberg Initiative DAF

European Research Council

DZHK

Helmholtz Zentrum München, funding program “Physician Scientists for Groundbreaking Projects”

Publisher

Elsevier BV

Subject

Radiology Nuclear Medicine and imaging,Atomic and Molecular Physics, and Optics

Reference40 articles.

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3. Use of multispectral optoacoustic tomography to diagnose vascular malformations;Masthoff;JAMA Dermatol.,2018

4. Multispectral optoacoustic tomography of benign and malignant thyroid disorders – a pilot study;Roll;J. Nucl. Med.,2019

5. Non-invasive measurement of brown fat metabolism based on optoacoustic imaging of hemoglobin gradients;Reber;Cell Metab.,2018

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