AIMC Topic: Skin Neoplasms

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Transfer Contrastive Learning for Raman Spectroscopy Skin Cancer Tissue Classification.

IEEE journal of biomedical and health informatics Dec 5, 2024
Using Raman spectroscopy (RS) signals for skin cancer tissue classification has recently drawn significant attention, because of its non-invasive optical technique, which uses molecular structures and conformations within biological tissue for diagno...
Humans Spectrum Analysis, Raman Signal Processing, Computer-Assisted Skin Skin Neoplasms Deep Learning
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Going Smaller: Attention-based models for automated melanoma diagnosis.

Computers in biology and medicine Dec 4, 2024
Computational approaches offer a valuable tool to aid with the early diagnosis of melanoma by increasing both the speed and accuracy of doctors' decisions. The latest and best-performing approaches often rely on large ensemble models, with the number...
Humans Neural Networks, Computer Skin Neoplasms Dermoscopy Melanoma
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Hybrid deep learning-based skin cancer classification with RPO-SegNet for skin lesion segmentation.

Network (Bristol, England) Dec 3, 2024
Skin melanin lesions are typically identified as tiny patches on the skin, which are impacted by melanocyte cell overgrowth. The number of people with skin cancer is increasing worldwide. Accurate and timely skin cancer identification is critical to ...
Skin Neoplasms Deep Learning Humans Neural Networks, Computer Image Processing, Computer-Assisted
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Detection of basal cell carcinoma by machine learning-assisted ex vivo confocal laser scanning microscopy.

International journal of dermatology Dec 3, 2024
BACKGROUND: Ex vivo confocal laser scanning microscopy (EVCM) is an emerging imaging modality that enables near real-time histology of whole tissue samples. However, the adoption of EVCM into clinical routine is partly limited because the recognition...
Neural Networks, Computer Machine Learning Female Humans Microscopy, Confocal Sensitivity and Specificity Skin Neoplasms Proof of Concept Study ROC Curve Carcinoma, Basal Cell
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Deep Learning for Automated Segmentation of Basal Cell Carcinoma on Mohs Micrographic Surgery Frozen Section Slides.

Dermatologic surgery : official publication for American Society for Dermatologic Surgery [et al.] Dec 3, 2024
BACKGROUND: Deep learning has been used to classify basal cell carcinoma (BCC) on histopathologic images. Segmentation models, required for localization of tumor on Mohs surgery (MMS) frozen section slides, have yet to reach clinical utility.
Skin Neoplasms Frozen Sections Carcinoma, Basal Cell Mohs Surgery Sensitivity and Specificity Humans Deep Learning
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Classification of melanoma skin Cancer based on Image Data Set using different neural networks.

Scientific reports Nov 29, 2024
This paper aims to address the pressing issue of melanoma classification by leveraging advanced neural network models, specifically basic Convolutional Neural Networks (CNN), ResNet-18, and EfficientNet-B0. Our objectives encompass presenting and eva...
Skin Neoplasms Image Processing, Computer-Assisted Algorithms Humans Image Interpretation, Computer-Assisted Melanoma Neural Networks, Computer
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Enhanced MobileNet for skin cancer image classification with fused spatial channel attention mechanism.

Scientific reports Nov 21, 2024
Skin Cancer, which leads to a large number of deaths annually, has been extensively considered as the most lethal tumor around the world. Accurate detection of skin cancer in its early stage can significantly raise the survival rate of patients and r...
Deep Learning Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Skin Neoplasms Humans Machine Learning Dermoscopy Neural Networks, Computer Algorithms
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Advancing dermoscopy through a synthetic hair benchmark dataset and deep learning-based hair removal.

Journal of biomedical optics Nov 19, 2024
SIGNIFICANCE: Early detection of melanoma is crucial for improving patient outcomes, and dermoscopy is a critical tool for this purpose. However, hair presence in dermoscopic images can obscure important features, complicating the diagnostic process....
Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Hair Removal Dermoscopy Melanoma Hair Humans Deep Learning Skin Neoplasms Neural Networks, Computer
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Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images.

Sensors (Basel, Switzerland) Nov 12, 2024
Skin cancer is the most common type of cancer in the United States and is estimated to affect one in five Americans. Recent advances have demonstrated strong performance on skin cancer detection, as exemplified by state of the art performance in the ...
Algorithms Skin Skin Neoplasms Humans Melanoma ROC Curve Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted
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Transforming Skin Cancer Diagnosis: A Deep Learning Approach with the Ham10000 Dataset.

Cancer investigation Nov 10, 2024
Skin cancer (SC) is one of the three most common cancers worldwide. Melanoma has the deadliest potential to spread to other parts of the body among all SCs. For SC treatments to be effective, early detection is essential. The high degree of similarit...
Carcinoma, Basal Cell Deep Learning Melanoma Skin Neoplasms Humans
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