Discriminating healthy from tumor tissue in breast lumpectomy specimens using deep learning-based hyperspectral imaging

Discriminating healthy from tumor tissue in breast lumpectomy specimens using deep learning-based hyperspectral imaging

Achieving an adequate resection margin during breast-conserving surgery remains challenging due to the lack of intraoperative feedback. Here, we evaluated the use of hyperspectral imaging to discriminate healthy tissue from tumor tissue in lumpectomy specimens. We first used a dataset obtained on ti...

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Bibliographic Details
Main Authors: Dashtbozorg, B. (Author), de Kruif, N. (Author), Duijnhoven, F.V.A.N (Author), Geldof, F. (Author), Jong, L.-J.S (Author), Ruers, T.J.M (Author), Sanders, J. (Author), Sterenborg, H.J.C.M (Author), Veluponnar, D. (Author), Vrancken Peeters, M.-J.T.F.D (Author)
Format: Article
Language:English
Published: Optica Publishing Group (formerly OSA) 2022
Subjects:
article
breast
Breast-conserving surgery
controlled study
convolutional neural network
Convolutional neural network
Convolutional neural networks
deep learning
Deep learning
Healthy tissues
human
human experiment
human tissue
HyperSpectral
hyperspectral imaging
Hyperspectral imaging
Intra-operative
lumpectomy
Lumpectomy specimen
Medical imaging
Spectroscopy
surgical margin
tissue slice
Tissue slice
Tumors
Tumour tissue
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