AIMC Topic: Skin Neoplasms

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Technological advances for the detection of melanoma: Advances in diagnostic techniques.

Journal of the American Academy of Dermatology
Managing the balance between accurately identifying early stage melanomas while avoiding obtaining biopsy specimens of benign lesions (ie, overbiopsy) is the major challenge of melanoma detection. Decision making can be especially difficult in patien...

Perioperative margin detection in basal cell carcinoma using a deep learning framework: a feasibility study.

International journal of computer assisted radiology and surgery
PURPOSE: Basal cell carcinoma (BCC) is the most commonly diagnosed cancer and the number of diagnosis is growing worldwide due to increased exposure to solar radiation and the aging population. Reduction of positive margin rates when removing BCC lea...

New Auxiliary Function with Properties in Nonsmooth Global Optimization for Melanoma Skin Cancer Segmentation.

BioMed research international
In this paper, an algorithm is introduced to solve the global optimization problem for melanoma skin cancer segmentation. The algorithm is based on the smoothing of an auxiliary function that is constructed using a known local minimizer and smoothed ...

A machine learning algorithm for simulating immunohistochemistry: development of SOX10 virtual IHC and evaluation on primarily melanocytic neoplasms.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Immunohistochemistry (IHC) is a diagnostic technique used throughout pathology. A machine learning algorithm that could predict individual cell immunophenotype based on hematoxylin and eosin (H&E) staining would save money, time, and reduce tissue co...

Skin Lesion Segmentation from Dermoscopic Images Using Convolutional Neural Network.

Sensors (Basel, Switzerland)
Clinical treatment of skin lesion is primarily dependent on timely detection and delimitation of lesion boundaries for accurate cancerous region localization. Prevalence of skin cancer is on the higher side, especially that of melanoma, which is aggr...

DePicT Melanoma Deep-CLASS: a deep convolutional neural networks approach to classify skin lesion images.

BMC bioinformatics
BACKGROUND: Melanoma results in the vast majority of skin cancer deaths during the last decades, even though this disease accounts for only one percent of all skin cancers' instances. The survival rates of melanoma from early to terminal stages is mo...

Artificial neural networks allow response prediction in squamous cell carcinoma of the scalp treated with radiotherapy.

Journal of the European Academy of Dermatology and Venereology : JEADV
BACKGROUND: Epithelial neoplasms of the scalp account for approximately 2% of all skin cancers and for about 10-20% of the tumours affecting the head and neck area. Radiotherapy is suggested for localized cutaneous squamous cell carcinomas (cSCC) wit...

Towards Interpretable Skin Lesion Classification with Deep Learning Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Skin disease is a prevalent condition all over the world. Computer vision-based technology for automatic skin lesion classification holds great promise as an effective screening tool for early diagnosis. In this paper, we propose an accurate and inte...