A survey on deep learning in medical image analysis
Deep learning algorithms, in particular convolutional networks, have rapidly become a
methodology of choice for analyzing medical images. This paper reviews the major deep …
methodology of choice for analyzing medical images. This paper reviews the major deep …
Image-based artificial intelligence in wound assessment: a systematic review
Significance: Accurately predicting wound healing trajectories is difficult for wound care
clinicians due to the complex and dynamic processes involved in wound healing. Wound …
clinicians due to the complex and dynamic processes involved in wound healing. Wound …
[HTML][HTML] Recognition of ischaemia and infection in diabetic foot ulcers: Dataset and techniques
Recognition and analysis of Diabetic Foot Ulcers (DFU) using computerized methods is an
emerging research area with the evolution of image-based machine learning algorithms …
emerging research area with the evolution of image-based machine learning algorithms …
Robust methods for real-time diabetic foot ulcer detection and localization on mobile devices
Current practice for diabetic foot ulcers (DFU) screening involves detection and localization
by podiatrists. Existing automated solutions either focus on segmentation or classification. In …
by podiatrists. Existing automated solutions either focus on segmentation or classification. In …
Dual cross-attention for medical image segmentation
Abstract We propose Dual Cross-Attention (DCA), a simple yet effective attention module
that enhances skip-connections in U-Net-based architectures for medical image …
that enhances skip-connections in U-Net-based architectures for medical image …
Segmentation of the proximal femur from MR images using deep convolutional neural networks
Magnetic resonance imaging (MRI) has been proposed as a complimentary method to
measure bone quality and assess fracture risk. However, manual segmentation of MR …
measure bone quality and assess fracture risk. However, manual segmentation of MR …
Fully automatic wound segmentation with deep convolutional neural networks
Acute and chronic wounds have varying etiologies and are an economic burden to
healthcare systems around the world. The advanced wound care market is expected to …
healthcare systems around the world. The advanced wound care market is expected to …
Multiclass wound image classification using an ensemble deep CNN-based classifier
Acute and chronic wounds are a challenge to healthcare systems around the world and
affect many people's lives annually. Wound classification is a key step in wound diagnosis …
affect many people's lives annually. Wound classification is a key step in wound diagnosis …
[HTML][HTML] Detect-and-segment: A deep learning approach to automate wound image segmentation
Chronic wounds significantly impact quality of life. They can rapidly deteriorate and require
close monitoring of healing progress. Image-based wound analysis is a way of objectively …
close monitoring of healing progress. Image-based wound analysis is a way of objectively …
Semi-supervised segmentation of lesion from breast ultrasound images with attentional generative adversarial network
Background and objective Automatic segmentation of breast lesion from ultrasound images
is a crucial module for the computer aided diagnostic systems in clinical practice. Large …
is a crucial module for the computer aided diagnostic systems in clinical practice. Large …