A comprehensive survey of deep learning research on medical image analysis with focus on transfer learning
This survey aims to identify commonly used methods, datasets, future trends, knowledge
gaps, constraints, and limitations in the field to provide an overview of current solutions used …
gaps, constraints, and limitations in the field to provide an overview of current solutions used …
Medical image segmentation with domain adaptation: a survey
Deep learning (DL) has shown remarkable success in various medical imaging data
analysis applications. However, it remains challenging for DL models to achieve good …
analysis applications. However, it remains challenging for DL models to achieve good …
Adaptive refining-aggregation-separation framework for unsupervised domain adaptation semantic segmentation
Unsupervised domain adaptation has attracted widespread attention as a promising method
to solve the labeling difficulties of semantic segmentation tasks. It trains a segmentation …
to solve the labeling difficulties of semantic segmentation tasks. It trains a segmentation …
Design and implementation of convolutional neural networks accelerator based on multidie
Q Song, J Zhang, L Sun, G ** - IEEE Access, 2022 - ieeexplore.ieee.org
To achieve real-time object detection tasks with high throughput and low latency, this paper
proposes a multi-die hardware accelerator architecture. It implements three accelerators on …
proposes a multi-die hardware accelerator architecture. It implements three accelerators on …
Automated biomedical image classification using multi-scale dense dilated semi-supervised u-net with cnn architecture
Biomedical research heavily relies on automated image classification to enhance
understanding of protein structure and function. This study proposes a novel approach for …
understanding of protein structure and function. This study proposes a novel approach for …
MBDA-Net: Multi-source boundary-aware prototype alignment domain adaptation for polyp segmentation
J Yan, H Zhu, T Hou, N Chen, W Lu, Y Wang… - … Signal Processing and …, 2024 - Elsevier
Accurate segmentation of polyps in colonoscopy images is important for the prevention and
treatment of colorectal cancer. However, samples collected from different centers often …
treatment of colorectal cancer. However, samples collected from different centers often …
Improved Two-Stage Transfer Learning Approach for ViT-Based Myocardial Infarction Detection
Myocardial infarction (MI) is a critical cardiovascular condition requiring precise diagnosis.
Accurate segmentation of myocardial pathologies in cardiac magnetic resonance (CMR) …
Accurate segmentation of myocardial pathologies in cardiac magnetic resonance (CMR) …
[HTML][HTML] Automatic vessel segmentation and reformation of non-contrast coronary magnetic resonance angiography using transfer learning-based three-dimensional …
L Lin, Y Zheng, Y Li, D Jiang, J Cao, J Wang… - Journal of …, 2025 - Elsevier
Background Coronary magnetic resonance angiography (CMRA) presents distinct
advantages, but its reliance on manual image post-processing is labor-intensive and …
advantages, but its reliance on manual image post-processing is labor-intensive and …
Improved image semantic segmentation with domain adaptation for mechanical parts
X XIE, Y HUANG, T WAN, L XU, F HU - Mechanical Engineering …, 2022 - jstage.jst.go.jp
Non-contact detection methods based on computer vision are widely used in industrial
production. When collecting images, different light source schemes are often used to meet …
production. When collecting images, different light source schemes are often used to meet …