Artificial intelligence-based approaches to reflectance confocal microscopy image analysis in dermatology

AM Malciu, M Lupu, VM Voiculescu - Journal of Clinical Medicine, 2022 - mdpi.com
Reflectance confocal microscopy (RCM) is a non-invasive imaging method designed to
identify various skin diseases. Confocal based diagnosis may be subjective due to the …

Automating reflectance confocal microscopy image analysis for dermatological research: a review

I Lboukili, G Stamatas… - Journal of Biomedical …, 2022 - spiedigitallibrary.org
Significance: Reflectance confocal microscopy (RCM) is a noninvasive, in vivo technology
that offers near histopathological resolution at the cellular level. It is useful in the study of …

Segmentation of cellular patterns in confocal images of melanocytic lesions in vivo via a multiscale encoder-decoder network (MED-Net)

K Kose, A Bozkurt, C Alessi-Fox, M Gill, C Longo… - Medical image …, 2021 - Elsevier
In-vivo optical microscopy is advancing into routine clinical practice for non-invasively
guiding diagnosis and treatment of cancer and other diseases, and thus beginning to reduce …

An Intelligent Mechanism to Detect Multi-Factor Skin Cancer

A Siddique, K Shaukat, T Jan - Diagnostics, 2024 - mdpi.com
Deep learning utilizing convolutional neural networks (CNNs) stands out among the state-of-
the-art procedures in PC-supported medical findings. The method proposed in this paper …

AK-DL: A shallow neural network model for diagnosing actinic keratosis with better performance than deep neural networks

L Wang, A Chen, Y Zhang, X Wang, Y Zhang, Q Shen… - Diagnostics, 2020 - mdpi.com
Actinic keratosis (AK) is one of the most common precancerous skin lesions, which is easily
confused with benign keratosis (BK). At present, the diagnosis of AK mainly depends on …

Convolutional neural network approach to classify skin lesions using reflectance confocal microscopy

M Wodzinski, A Skalski, A Witkowski… - 2019 41st Annual …, 2019 - ieeexplore.ieee.org
We propose an approach based on a convolutional neural network to classify skin lesions
using the reflectance confocal microscopy (RCM) mosaics. Skin cancers are the most …

Deep learning on reflectance confocal microscopy improves Raman spectral diagnosis of basal cell carcinoma

M Chen, X Feng, MC Fox… - Journal of …, 2022 - spiedigitallibrary.org
Significance: Raman spectroscopy (RS) provides an automated approach for assisting Mohs
micrographic surgery for skin cancer diagnosis; however, the specificity of RS is limited by …

Skin strata delineation in reflectance confocal microscopy images using recurrent convolutional networks with attention

A Bozkurt, K Kose, J Coll-Font, C Alessi-Fox… - Scientific Reports, 2021 - nature.com
Reflectance confocal microscopy (RCM) is an effective non-invasive tool for cancer
diagnosis. However, acquiring and reading RCM images requires extensive training and …

Utilizing deep learning for dermal matrix quality assessment on in vivo line‐field confocal optical coherence tomography images

J Breugnot, P Rouaud‐Tinguely… - Skin Research and …, 2023 - Wiley Online Library
Background Line‐field confocal optical coherence tomography (LC‐OCT) is an imaging
technique providing non‐invasive “optical biopsies” with an isotropic spatial resolution of∼ …

Computer-aided diagnosis of melanoma subtypes using reflectance confocal images

A Mandal, S Priyam, HH Chan, BM Gouveia, P Guitera… - Cancers, 2023 - mdpi.com
Simple Summary Melanoma is a serious public health concern that causes significant illness
and death, especially among young adults in Australia and New Zealand. Reflectance …