A comparative study of deep learning architectures on melanoma detection

SH Kassani, PH Kassani - Tissue and Cell, 2019 - Elsevier
Melanoma is the most aggressive type of skin cancer, which significantly reduces the life
expectancy. Early detection of melanoma can reduce the morbidity and mortality associated …

The melanoma skin cancer detection and classification using support vector machine

H Alquran, IA Qasmieh, AM Alqudah… - 2017 IEEE Jordan …, 2017 - ieeexplore.ieee.org
Melanoma skin cancer detection at an early stage is crucial for an efficient treatment.
Recently, it is well known that, the most dangerous form of skin cancer among the other …

Melanoma is skin deep: a 3D reconstruction technique for computerized dermoscopic skin lesion classification

TY Satheesha, D Satyanarayana… - IEEE journal of …, 2017 - ieeexplore.ieee.org
Melanoma mortality rates are the highest amongst skin cancer patients. Melanoma is life
threating when it grows beyond the dermis of the skin. Hence, depth is an important factor to …

A deep convolutional neural network-based pigmented skin lesion classification application and experts evaluation

O Sevli - Neural Computing and Applications, 2021 - Springer
Pigmented skin lesions are common spots or growths on the skin that originate from
melanocyte cells. Skin cancer occurs as a result of the uncontrolled division of melanocyte …

Machine learning techniques for automated melanoma detection

E Vocaturo, D Perna, E Zumpano - 2019 IEEE International …, 2019 - ieeexplore.ieee.org
The malignant melanoma is one of the most aggressive forms of skin cancer. Modern
Dermatology recognizes early diagnosis as a fundamental role in reducing the mortality rate …

Classification of diabetic retinopathy based on hard exudates patterns, using images processing and SVM

F Cisneros-Guzmán, S Tovar-Arriaga… - … on Applications in …, 2019 - ieeexplore.ieee.org
Diabetic retinopathy (DR) is an ocular disease very common on diabetic patients. It is
developed when the patient present a high level of glucose in blood which in consequence …

[PDF][PDF] Statistical analysis of skin cancer image–a case study

S Achakanalli, G Sadashivappa - International Journal of Electronics …, 2014 - academia.edu
Skin cancers account for more than 40% of all malignancies all over the world, and the
incidence continues to rise. This increase is attributed to environmental exposure, principally …

Skin cancer detection using machine learning framework with mobile application

ME Ananna, J Nayeem, MJ Alam… - 2023 7th International …, 2023 - ieeexplore.ieee.org
A notable increase in skin cancer mortality, one of the most lethal kinds of cancer, has been
caused by a lack of awareness of warning signals and preventative measures. The need for …

A clinical decision support system for micro panoramic melanoma detection and grading using soft computing technique

M Reshma, BP Shan - Measurement, 2020 - Elsevier
Computer aided algorithms plays pivotal role in disease diagnosis and treatment planning
for therapeutic applications. This research work proposes a clinical decision support system …

IVE-MDNet: Intensity Value Estimation Model Combined with a Transfer Learning Approach for Melanoma Skin Cancer Diagnosis

NIM Ashafuddula, R Islam - SN Computer Science, 2024 - Springer
The percentage of people affected by skin cancer has been rising in recent years.
Melanoma is identified as the most dangerous and life-threatening among the three types of …