[HTML][HTML] A Comprehensive Survey of Deep Learning Approaches in Image Processing
The integration of deep learning (DL) into image processing has driven transformative
advancements, enabling capabilities far beyond the reach of traditional methodologies. This …
advancements, enabling capabilities far beyond the reach of traditional methodologies. This …
MaxViT-UNet: Multi-axis attention for medical image segmentation
Since their emergence, Convolutional Neural Networks (CNNs) have made significant
strides in medical image analysis. However, the local nature of the convolution operator may …
strides in medical image analysis. However, the local nature of the convolution operator may …
EG-UNETR: An edge-guided liver tumor segmentation network based on cross-level interactive transformer
D Cheng, Z Zhou, J Zhang - Biomedical Signal Processing and Control, 2024 - Elsevier
Liver cancer diagnosis and treatment planning rely heavily on accurate liver tumor
segmentation from CT images. Traditional methods still face the problems of blurred tumor …
segmentation from CT images. Traditional methods still face the problems of blurred tumor …
[HTML][HTML] Convolutional Neural Network–Vision Transformer Architecture with Gated Control Mechanism and Multi-Scale Fusion for Enhanced Pulmonary Disease …
O Chibuike, X Yang - Diagnostics, 2024 - mdpi.com
Background/Objectives: Vision Transformers (ViTs) and convolutional neural networks
(CNNs) have demonstrated remarkable performances in image classification, especially in …
(CNNs) have demonstrated remarkable performances in image classification, especially in …
[HTML][HTML] RailTrack-DaViT: A Vision Transformer-Based Approach for Automated Railway Track Defect Detection
Railway track defects pose significant safety risks and can lead to accidents, economic
losses, and loss of life. Traditional manual inspection methods are either time-consuming …
losses, and loss of life. Traditional manual inspection methods are either time-consuming …
FibroRegNet: A Regression Framework for the Pulmonary Fibrosis Prognosis Prediction Using a Convolutional Spatial Transformer Network
Predicting the growth of idiopathic pulmonary fibrosis (IPF) is crucial for effectively treating
patients affected by the disease. While the Forced Vital Capacity (FVC) serves as one of the …
patients affected by the disease. While the Forced Vital Capacity (FVC) serves as one of the …
A transformer-guided cross-modality adaptive feature fusion framework for esophageal gross tumor volume segmentation
Y Yue, N Li, G Zhang, W **ng, Z Zhu, X Liu… - Computer Methods and …, 2024 - Elsevier
Abstract Background and Objective Accurate segmentation of esophageal gross tumor
volume (GTV) indirectly enhances the efficacy of radiotherapy for patients with esophagus …
volume (GTV) indirectly enhances the efficacy of radiotherapy for patients with esophagus …
A Microvascular Segmentation Network Based on Pyramidal Attention Mechanism
H Zhang, W Fang, J Li - Sensors, 2024 - mdpi.com
The precise segmentation of retinal vasculature is crucial for the early screening of various
eye diseases, such as diabetic retinopathy and hypertensive retinopathy. Given the complex …
eye diseases, such as diabetic retinopathy and hypertensive retinopathy. Given the complex …
A Novel Feature Map Enhancement Technique Integrating Residual CNN and Transformer for Alzheimer Diseases Diagnosis
SH Khan - arxiv preprint arxiv:2405.12986, 2024 - arxiv.org
Alzheimer diseases (ADs) involves cognitive decline and abnormal brain protein
accumulation, necessitating timely diagnosis for effective treatment. Therefore, CAD systems …
accumulation, necessitating timely diagnosis for effective treatment. Therefore, CAD systems …