Weakly-supervised deep learning for ultrasound diagnosis of breast cancer

Conventional deep learning (DL) algorithm requires full supervision of annotating the region of interest (ROI) that is laborious and often biased. We aimed to develop a weakly-supervised DL algorithm that diagnosis breast cancer at ultrasound without image annotation. Weakly-supervised DL algorithms...

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Vydáno v:	Scientific reports Ročník 11; číslo 1; s. 24382 - 10
Hlavní autoři:	Kim, Jaeil, Kim, Hye Jung, Kim, Chanho, Lee, Jin Hwa, Kim, Keum Won, Park, Young Mi, Kim, Hye Won, Ki, So Yeon, Kim, You Me, Kim, Won Hwa
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 21.12.2021 Nature Publishing Group Nature Portfolio
Témata:	631/67 631/67/1347 692/4028 692/700 692/700/1421/1860 Adolescent Adult Aged Aged, 80 and over Algorithms Annotations Automation Breast - diagnostic imaging Breast - pathology Breast cancer Breast Neoplasms - diagnosis Breast Neoplasms - diagnostic imaging Case-Control Studies Deep Learning Diagnosis, Differential Differential diagnosis Female Follow-Up Studies Humanities and Social Sciences Humans Image Interpretation, Computer-Assisted - methods Localization Middle Aged multidisciplinary Neural Networks, Computer Prognosis Retrospective Studies ROC Curve Science Science (multidisciplinary) Ultrasonic imaging Ultrasonography, Mammary - methods Ultrasound Young Adult United States > US
ISSN:	2045-2322, 2045-2322
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