A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation

H Jiang, Z Diao, T Shi, Y Zhou, F Wang, W Hu… - Computers in Biology …, 2023 - Elsevier
Deep learning-based methods have become the dominant methodology in medical image
processing with the advancement of deep learning in natural image classification, detection …

[HTML][HTML] Trustworthy clinical AI solutions: a unified review of uncertainty quantification in deep learning models for medical image analysis

B Lambert, F Forbes, S Doyle, H Dehaene… - Artificial Intelligence in …, 2024 - Elsevier
The full acceptance of Deep Learning (DL) models in the clinical field is rather low with
respect to the quantity of high-performing solutions reported in the literature. End users are …

Semi-supervised medical image segmentation via cross teaching between cnn and transformer

X Luo, M Hu, T Song, G Wang… - … conference on medical …, 2022 - proceedings.mlr.press
Recently, deep learning with Convolutional Neural Networks (CNNs) and Transformers has
shown encouraging results in fully supervised medical image segmentation. However, it is …

Current and emerging trends in medical image segmentation with deep learning

PH Conze, G Andrade-Miranda… - … on Radiation and …, 2023 - ieeexplore.ieee.org
In recent years, the segmentation of anatomical or pathological structures using deep
learning has experienced a widespread interest in medical image analysis. Remarkably …

Generative adversarial networks in medical image segmentation: A review

S Xun, D Li, H Zhu, M Chen, J Wang, J Li… - Computers in biology …, 2022 - Elsevier
Abstract Purpose Since Generative Adversarial Network (GAN) was introduced into the field
of deep learning in 2014, it has received extensive attention from academia and industry …

[KNYGA][B] Deep learning for medical image analysis

SK Zhou, H Greenspan, D Shen - 2023 - books.google.com
Deep Learning for Medical Image Analysis, Second Edition is a great learning resource for
academic and industry researchers and graduate students taking courses on machine …

A review of uncertainty quantification in medical image analysis: Probabilistic and non-probabilistic methods

L Huang, S Ruan, Y ** review
TJ Loftus, B Shickel, MM Ruppert, JA Balch… - PLOS digital …, 2022 - journals.plos.org
Mistrust is a major barrier to implementing deep learning in healthcare settings. Entrustment
could be earned by conveying model certainty, or the probability that a given model output is …

Deep learning for rare disease: A sco** review

J Lee, C Liu, J Kim, Z Chen, Y Sun, JR Rogers… - Journal of biomedical …, 2022 - Elsevier
Although individually rare, collectively more than 7,000 rare diseases affect about 10% of
patients. Each of the rare diseases impacts the quality of life for patients and their families …

[HTML][HTML] Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging

R Osuala, K Kushibar, L Garrucho, A Linardos… - Medical Image …, 2023 - Elsevier
Despite technological and medical advances, the detection, interpretation, and treatment of
cancer based on imaging data continue to pose significant challenges. These include inter …