Pattern Classification Approaches for Breast Cancer Identification via MRI: State-Of-The-Art and Vision for the Future
Mining algorithms for Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) of breast tissue are discussed. The algorithms are based on recent advances in multi-dimensional signal processing and aim to advance current state-of-the-art computer-aided detection and analysis of breast tumours...
Main Authors: | Xiao-Xia Yin, Lihua Yin, Sillas Hadjiloucas |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-10-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/10/20/7201 |
Similar Items
-
Semi-supervised vision transformer with adaptive token sampling for breast cancer classification
by: Wei Wang, et al.
Published: (2022-07-01) -
CLASSIFICATION BASED ON SEMI-SUPERVISED LEARNING: A REVIEW
by: Aska Ezadeen Mehyadin, et al.
Published: (2021-05-01) -
LMGAN: Linguistically Informed Semi-Supervised GAN with Multiple Generators
by: Whanhee Cho, et al.
Published: (2022-11-01) -
Survey of Multi-label Classification Based on Supervised and Semi-supervised Learning
by: WU Hong-xin, HAN Meng, CHEN Zhi-qiang, ZHANG Xi-long, LI Mu-hang
Published: (2022-08-01) -
A survey of large-scale graph-based semi-supervised classification algorithms
by: Yunsheng Song, et al.
Published: (2022-06-01)