TrEnD: A transformer‐based encoder‐decoder model with adaptive patch embedding for mass segmentation in mammograms

Background Breast cancer is one of the most prevalent malignancies diagnosed in women. Mammogram inspection in the search and delineation of breast tumors is an essential prerequisite for a reliable diagnosis. However, analyzing mammograms by radiologists is time‐consuming and prone to errors. There...

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Bibliographic Details
Published in:	Medical physics (Lancaster) Vol. 50; no. 5; pp. 2884 - 2899
Main Authors:	Liu, Dongdong, Wu, Bo, Li, Changbo, Sun, Zheng, Zhang, Nan
Format:	Journal Article
Language:	English
Published:	United States 01.05.2023
Subjects:	Animals attention mechanism breast mass Breast Neoplasms - diagnostic imaging Computer Systems Female Hominidae Humans Image Processing, Computer-Assisted mammograms Mammography Radiologists segmentation transformer breast mass transformer segmentation mammograms attention mechanism
ISSN:	0094-2405, 2473-4209, 2473-4209
Online Access:	Get full text
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