A survey on deep learning for skin lesion segmentation

Z Mirikharaji, K Abhishek, A Bissoto, C Barata… - Medical Image …, 2023 - Elsevier
Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

[HTML][HTML] SaltGAN: A feature-infused and loss-controlled generative adversarial network with preserved checkpoints for evolving histopathology images

ON Oyelade, H Wang, SA Adewuyi - Biomedical Signal Processing and …, 2024 - Elsevier
The use of natural phenomena as inspiration to address real-life problems has become an
increasingly popular research approach. In the medical domain, generative adversarial …

Dense Mesh RCNN: assessment of human skin burn and burn depth severity

C Pabitha, B Vanathi - The Journal of Supercomputing, 2024 - Springer
Accurate assessment and classification of burn severity have gained research interest in
burn management, and delays in treatment increase the risk of human lives. Many research …

Syn3DWound: A Synthetic Dataset for 3D Wound Bed Analysis

L Lebrat, R Santa Cruz, R Chierchia… - 2024 IEEE …, 2024 - ieeexplore.ieee.org
Wound management poses a significant challenge, particularly for bedridden patients and
the elderly. Accurate diagnostic and healing monitoring can significantly benefit from …

Addressing fairness and data limitations in dermatological diagnosis through color-invariant representation learning and synthetic data generation

A Pakzad - 2024 - summit.sfu.ca
While deep learning-based approaches have demonstrated expert-level performance in
dermatological diagnosis tasks, they rely on a data-driven learning paradigm that requires …

Representation and synthesis of 3D biomedical visual data

A Sinha - 2024 - summit.sfu.ca
The success of deep learning (DL) on a wide range of computer vision tasks can be
attributed to the availability of large-scale annotated datasets, such as ImageNet and MS …