AIMC Topic: Carcinoma, Basal Cell
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Basal Cell Carcinoma Diagnosis with Fusion of Deep Learning and Telangiectasia Features.
Journal of imaging informatics in medicine
Feb 8, 2024
In recent years, deep learning (DL) has been used extensively and successfully to diagnose different cancers in dermoscopic images. However, most approaches lack clinical inputs supported by dermatologists that could aid in higher accuracy and explai...
SkinViT: A transformer based method for Melanoma and Nonmelanoma classification.
PloS one
Dec 27, 2023
Over the past few decades, skin cancer has emerged as a major global health concern. The efficacy of skin cancer treatment greatly depends upon early diagnosis and effective treatment. The automated classification of Melanoma and Nonmelanoma is quite...
A deep learning algorithm to detect cutaneous squamous cell carcinoma on frozen sections in Mohs micrographic surgery: A retrospective assessment.
Experimental dermatology
Oct 21, 2023
Intraoperative margin analysis is crucial for the successful removal of cutaneous squamous cell carcinomas (cSCC). Artificial intelligence technologies (AI) have previously demonstrated potential for facilitating rapid and complete tumour removal usi...
Applying an artificial intelligence deep learning approach to routine dermatopathological diagnosis of basal cell carcinoma.
Journal der Deutschen Dermatologischen Gesellschaft = Journal of the German Society of Dermatology : JDDG
Oct 9, 2023
BACKGROUND: Institutes of dermatopathology are faced with considerable challenges including a continuously rising numbers of submitted specimens and a shortage of specialized health care practitioners. Basal cell carcinoma (BCC) is one of the most co...
Deep learning-based semantic segmentation of non-melanocytic skin tumors in whole-slide histopathological images.
Experimental dermatology
Apr 5, 2023
Basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) are the two most common skin cancer and impose a huge medical burden on society. Histopathological examination based on whole-slide images (WSIs) remains to be the confirmatory diagnostic m...
A deep-learning algorithm to localize basal cell carcinoma foci on Mohs surgery frozen sections.
Journal of the European Academy of Dermatology and Venereology : JEADV
Jan 24, 2023
Multi-site cross-organ calibrated deep learning (MuSClD): Automated diagnosis of non-melanoma skin cancer.
Medical image analysis
Nov 24, 2022
Although deep learning (DL) has demonstrated impressive diagnostic performance for a variety of computational pathology tasks, this performance often markedly deteriorates on whole slide images (WSI) generated at external test sites. This phenomenon ...
Real-time, in vivo skin cancer triage by laser-induced plasma spectroscopy combined with a deep learning-based diagnostic algorithm.
Journal of the American Academy of Dermatology
Jun 22, 2022
BACKGROUND: Although various skin cancer detection devices have been proposed, most of them are not used owing to their insufficient diagnostic accuracies. Laser-induced plasma spectroscopy (LIPS) can noninvasively extract biochemical information of ...
A deep learning approach to detect blood vessels in basal cell carcinoma.
Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI)
May 25, 2022
PURPOSE: Blood vessels called telangiectasia are visible in skin lesions with the aid of dermoscopy. Telangiectasia are a pivotal identifying feature of basal cell carcinoma. These vessels appear thready, serpiginous, and may also appear arborizing, ...
Deep learning data augmentation for Raman spectroscopy cancer tissue classification.
Scientific reports
Dec 13, 2021
Recently, Raman Spectroscopy (RS) was demonstrated to be a non-destructive way of cancer diagnosis, due to the uniqueness of RS measurements in revealing molecular biochemical changes between cancerous vs. normal tissues and cells. In order to design...
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