DDCNN-F: double decker convolutional neural network'F'feature fusion as a medical image classification framework

N Veeramani, P Jayaraman, R Krishankumar… - Scientific Reports, 2024 - nature.com
Melanoma is a severe skin cancer that involves abnormal cell development. This study aims
to provide a new feature fusion framework for melanoma classification that includes a novel …

Spatial feature and resolution maximization GAN for bone suppression in chest radiographs

G Rani, A Misra, VS Dhaka, E Zumpano… - Computer Methods and …, 2022 - Elsevier
Abstract Background and Objective: Chest radiographs (CXR) are in great demand for
visualizing the pathology of the lungs. However, the appearance of bones in the lung region …

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 …

Detection of melanoma with hybrid learning method by removing hair from dermoscopic images using image processing techniques and wavelet transform

Ç Suiçmez, HT Kahraman, A Suiçmez, C Yılmaz… - … Signal Processing and …, 2023 - Elsevier
Melanoma is one of the most dangerous types of skin cancer. Detecting melanoma is
complicated and takes too much time, which doctors and healthcare professionals …

[PDF][PDF] Melanoma detection using color and texture features in computer vision systems

A Fuduli, P Veltri, E Vocaturo… - Advances in Science …, 2019 - researchgate.net
All forms of skin cancer are becoming widespread. These forms of cancer, and melanoma in
particular, are insidious and aggressive and if not treated promptly can be lethal to humans …

Dangerousness of dysplastic nevi: A multiple instance learning solution for early diagnosis

E Vocaturo, E Zumpano - 2019 IEEE International Conference …, 2019 - ieeexplore.ieee.org
Malignant melanoma is responsible for the highest number of deaths related to skin lesions.
However, early diagnosis may allow positive treatment of this terrible form of cancer. The …

The contribution of AI in the detection of the Diabetic Retinopathy

E Vocaturo, E Zumpano - 2020 IEEE International Conference …, 2020 - ieeexplore.ieee.org
The prevalence of diabetes is rising worldwide and in the last two decades, blindness and
low vision due to diabetic eye complications have greatly increased. International Diabetes …

Analysis of Automated Melanoma Detection Utilizing Machine Learning and Deep Learning Techniques: A Review

A Ullah, FBA Razak, R Hassnae… - … Journal of Image and …, 2024 - World Scientific
Skin cancer is described as an abnormal, exponential growth of skin cells that originate from
melanocytes due to DNA impair or damage. It is threatening because of its ability to …

Federated Learning Applications for Breast Cancer

L Caroprese, T Ruga, E Vocaturo… - … on Bioinformatics and …, 2023 - ieeexplore.ieee.org
Breast cancer stands as the leading cause of mortality among women worldwide,
encompassing all types of cancer. It can affect women of all age groups post-puberty in any …

Diabetic retinopathy images classification via multiple instance learning

E Vocaturo, E Zumpano - 2021 IEEE/ACM Conference on …, 2021 - ieeexplore.ieee.org
Diabetic retinopathy (DR) is a complication of diabetes that affects eyes. It is among the
primary cause of blindness and low vision and originates from the damage of the blood …