Transition of traditional method to deep learning based computer-aided system for breast cancer using Automated Breast Ultrasound System (ABUS) images: a review
Author:
Funder
Graduate Putra Initiative Grant, IPS
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Linguistics and Language,Language and Linguistics
Link
https://link.springer.com/content/pdf/10.1007/s10462-023-10511-6.pdf
Reference120 articles.
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2. Bian C, Lee R, Chou YH, Cheng JZ (2017) Boundary regularized convolutional neural network for layer parsing of breast anatomy in automated whole breast ultrasound. In: International Conference on Medical Image Computing and Computer-Assisted Intervention, pp 259–266
3. Bluemke DA, Moy L, Bredella MA, Ertl-Wagner BB, Fowler KJ, Goh VJ, Halpern EF, Hess CP, Schiebler ML, Weiss CR (2020) Assessing radiology research on artificial intelligence: a brief guide for authors, reviewers, and readers from the radiology editorial board. Radiology 294(3):487–489
4. Boca I, Ciurea AI, Ciortea CA, Dudea SM (2021) Pros and cons for automated breast ultrasound (ABUS): a narrative review. J Person Med 11(8):703
5. Burkett BJ, Hanemann CW (2016) A review of supplemental screening ultrasound for breast cancer: certain populations of women with dense breast tissue may benefit. Acad Radiol 23:1604–1609
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