AIMC Topic: Dermoscopy
Clear Filters Showing 141 to 150 of 181 articles
Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks.
IEEE journal of biomedical and health informatics
Dec 25, 2017
Automatic skin lesion segmentation on dermoscopic images is an essential step in computer-aided diagnosis of melanoma. However, this task is challenging due to significant variations of lesion appearances across different patients. This challenge is ...
Recognition of pigment network pattern in dermoscopy images based on fuzzy classification of pixels.
Computer methods and programs in biomedicine
Oct 7, 2017
BACKGROUND AND OBJECTIVE: One of the most relevant dermoscopic patterns is the pigment network. An innovative method of pattern recognition is presented for its detection in dermoscopy images.
Machine learning and melanoma: The future of screening.
Journal of the American Academy of Dermatology
Oct 6, 2017
Melanoma Classification on Dermoscopy Images Using a Neural Network Ensemble Model.
IEEE transactions on medical imaging
Dec 1, 2016
We develop a novel method for classifying melanocytic tumors as benign or malignant by the analysis of digital dermoscopy images. The algorithm follows three steps: first, lesions are extracted using a self-generating neural network (SGNN); second, f...
Unsupervised delineation of stratum corneum using reflectance confocal microscopy and spectral clustering.
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)
Aug 12, 2016
BACKGROUND: Measuring the thickness of the stratum corneum (SC) in vivo is often required in pharmacological, dermatological, and cosmetological studies. Reflectance confocal microscopy (RCM) offers a non-invasive imaging-based approach. However, RCM...
Computer-Aided Diagnosis of Micro-Malignant Melanoma Lesions Applying Support Vector Machines.
BioMed research international
Jun 13, 2016
Background. One of the fatal disorders causing death is malignant melanoma, the deadliest form of skin cancer. The aim of the modern dermatology is the early detection of skin cancer, which usually results in reducing the mortality rate and less exte...
Adaptable texture-based segmentation by variance and intensity for automatic detection of semitranslucent and pink blush areas 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)
Mar 16, 2016
BACKGROUND: Pink blush is a common feature in basal cell carcinoma (BCC). A related feature, semitranslucency, appears as smooth pink or orange regions resembling skin color. We introduce an automatic method for detection of these features based on s...
Real-time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location.
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)
Mar 22, 2015
BACKGROUND/PURPOSE: Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature ...
Four-class classification of skin lesions with task decomposition strategy.
IEEE transactions on bio-medical engineering
Aug 15, 2014
This paper proposes a new computer-aided method for the skin lesion classification applicable to both melanocytic skin lesions (MSLs) and nonmelanocytic skin lesions (NoMSLs). The computer-aided skin lesion classification has drawn attention as an ai...
Updated Techniques for Melanoma Diagnosis.
Dermatologic clinics
Jul 1, 2025
Melanoma, an aggressive skin cancer, requires timely diagnostics for improved patient outcomes. The ABCDE criteria-assessing asymmetry, borders, color, diameter, and evolution-serve as foundational guidelines for early detection. Non-invasive tools l...
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