Tubule-U-Net: a novel dataset and deep learning-based tubule segmentation framework in whole slide images of breast cancer

The tubule index is a vital prognostic measure in breast cancer tumor grading and is visually evaluated by pathologists. In this paper, a computer-aided patch-based deep learning tubule segmentation framework, named Tubule-U-Net, is developed and proposed to segment tubules in Whole Slide Images (WS...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Scientific reports Ročník 13; číslo 1; s. 128 - 11
Hlavní autori:	Tekin, Eren, Yazıcı, Çisem, Kusetogullari, Huseyin, Tokat, Fatma, Yavariabdi, Amir, Iheme, Leonardo Obinna, Çayır, Sercan, Bozaba, Engin, Solmaz, Gizem, Darbaz, Berkan, Özsoy, Gülşah, Ayaltı, Samet, Kayhan, Cavit Kerem, İnce, Ümit, Uzel, Burak
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	London Nature Publishing Group UK 04.01.2023 Nature Publishing Group Nature Portfolio
Predmet:	631/67/1347 639/705 Breast cancer Breast Neoplasms Breast Neoplasms - diagnostic imaging breast tumor Computer-Assisted Datasets Deep Learning diagnostic imaging Female human Humanities and Social Sciences Humans Image Processing Image Processing, Computer-Assisted - methods multidisciplinary procedures Science Science (multidisciplinary) Segmentation Semantics Tubules Tumors
ISSN:	2045-2322, 2045-2322
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!