AI-powered diagnosis of skin cancer: a contemporary review, open challenges and future research directions
Simple Summary The proposed research aims to provide a deep insight into the deep
learning and machine learning techniques used for diagnosing skin cancer. While …
learning and machine learning techniques used for diagnosing skin cancer. While …
Artificial intelligence and skin cancer
ML Wei, M Tada, A So, R Torres - Frontiers in Medicine, 2024 - frontiersin.org
Artificial intelligence is poised to rapidly reshape many fields, including that of skin cancer
screening and diagnosis, both as a disruptive and assistive technology. Together with the …
screening and diagnosis, both as a disruptive and assistive technology. Together with the …
[HTML][HTML] Generative models for color normalization in digital pathology and dermatology: Advancing the learning paradigm
Color medical images introduce an additional confounding factor compared to conventional
grayscale medical images: color variability. This variability can lead to inconsistent …
grayscale medical images: color variability. This variability can lead to inconsistent …
Skin lesion segmentation using two-phase cross-domain transfer learning framework
Abstract Background and Objective Deep learning (DL) models have been used for medical
imaging for a long time but they did not achieve their full potential in the past because of …
imaging for a long time but they did not achieve their full potential in the past because of …
[HTML][HTML] All you need is data preparation: A systematic review of image harmonization techniques in Multi-center/device studies for medical support systems
Abstract Background and Objectives Artificial intelligence (AI) models trained on multi-
centric and multi-device studies can provide more robust insights and research findings …
centric and multi-device studies can provide more robust insights and research findings …
A deep learning-based illumination transform for devignetting photographs of dermatological lesions
Photographs of skin lesions taken with standard digital cameras (macroscopic images) have
gained wide acceptance in dermatology. However, uneven background lighting caused by …
gained wide acceptance in dermatology. However, uneven background lighting caused by …
Detecting Skin Reactions in Epicutaneous Patch Testing with Deep Learning: An Evaluation of Pre-Processing and Modality Performance
Epicutaneous patch testing is a well-established diagnostic method for identifying
substances that may cause Allergic Contact Dermatitis (ACD), a common skin condition …
substances that may cause Allergic Contact Dermatitis (ACD), a common skin condition …
Increasing-margin adversarial (IMA) training to improve adversarial robustness of neural networks
Abstract Background and Objective: Deep neural networks (DNNs) are vulnerable to
adversarial noises. Adversarial training is a general and effective strategy to improve DNN …
adversarial noises. Adversarial training is a general and effective strategy to improve DNN …
Impact of artificial intelligence‐based color constancy on dermoscopical assessment of skin lesions: A comparative study
Background The quality of dermoscopic images is affected by lighting conditions, operator
experience, and device calibration. Color constancy algorithms reduce this variability by …
experience, and device calibration. Color constancy algorithms reduce this variability by …
[HTML][HTML] Enhanced tissue slide imaging in the complex domain via cross-explainable GAN for Fourier ptychographic microscopy
Achieving microscopy with large space-bandwidth products plays a key role in diagnostic
imaging and is widely significant in the overall field of clinical practice. Among quantitative …
imaging and is widely significant in the overall field of clinical practice. Among quantitative …