Deep learning extended depth-of-field microscope for fast and slide-free histology

Microscopic evaluation of resected tissue plays a central role in the surgical management of cancer. Because optical microscopes have a limited depth-of-field (DOF), resected tissue is either frozen or preserved with chemical fixatives, sliced into thin sections placed on microscope slides, stained,...

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Vydané v:	Proceedings of the National Academy of Sciences - PNAS Ročník 117; číslo 52; s. 33051
Hlavní autori:	Jin, Lingbo, Tang, Yubo, Wu, Yicheng, Coole, Jackson B, Tan, Melody T, Zhao, Xuan, Badaoui, Hawraa, Robinson, Jacob T, Williams, Michelle D, Gillenwater, Ann M, Richards-Kortum, Rebecca R, Veeraraghavan, Ashok
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States 29.12.2020
Predmet:	Algorithms Animals Biopsy - instrumentation Biopsy - methods Biopsy - standards Calibration Carcinoma - pathology Deep Learning Humans Image Processing, Computer-Assisted - instrumentation Image Processing, Computer-Assisted - methods Image Processing, Computer-Assisted - standards Microscopy, Fluorescence - instrumentation Microscopy, Fluorescence - methods Microscopy, Fluorescence - standards Mouth Neoplasms - pathology Swine deep learning end-to-end optimization pathology phase mask extended depth-of-field microscopy
ISSN:	1091-6490, 1091-6490
On-line prístup:	Zistit podrobnosti o prístupe
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