Skin cancer and melanoma

Virtual Issues
4 April 2023
28 April 2023
Export Citation(s)Download PDF(s)

Table of Contents

Melanoma segmentation: A framework of improved DenseNet77 and UNET convolutional neural network

Marriam Nawaz,  Tahira Nazir,  Momina Masood,  Farooq Ali,  Muhammad Attique Khan,  Usman Tariq,  Naveera Sahar,  Robertas Damaševičius, 
Free to Read

An accurate and noninvasive skin cancer screening based on imaging technique

Gunjan Rajput,  Shashank Agrawal,  Gopal Raut,  Santosh Kumar Vishvakarma, 

SLICACO: An automated novel hybrid approach for dermatoscopic melanocytic skin lesion segmentation

Lokesh Singh,  Rekh Ram Janghel,  Satya Prakash Sahu, 

Skin lesion segmentation using an improved framework of encoder-decoder based convolutional neural network

Ranpreet Kaur,  Hamid GholamHosseini,  Roopak Sinha, 

A hybrid feature fusion strategy for early fusion and majority voting for late fusion towards melanocytic skin lesion detection

Lokesh Singh,  Rekh Ram Janghel,  Satya Prakash Sahu, 

Skin lesion segmentation based on mask RCNN, Multi Atrous Full-CNN, and a geodesic method

Fatemeh Bagheri,  Mohammad Jafar Tarokh,  Majid Ziaratban, 

A novel hybrid artificial neural network technique for the early skin cancer diagnosis using color space conversions of original images

Salwan Tajjour,  Sonia Garg,  Shyam Singh Chandel,  Diksha Sharma, 

SegCaps: An efficient SegCaps network-based skin lesion segmentation in dermoscopic images

Gouse Mohiuddin Kosgiker,  Anupama Deshpande,  Anjum Kauser, 

Automated differentiation of skin melanocytes from keratinocytes in high-resolution histopathology images using a weakly-supervised deep-learning framework

Madan Parajuli,  Mohamed Shaban,  Thuy L. Phung, 

Skin lesion classification based on the VGG-16 fusion residual structure

Pu Yan,  Gang Wang,  Jie Chen,  Qingwei Tang,  Heng Xu, 

A computer-aided melanoma detection using deep learning and an improved African vulture optimization algorithm

Libing Hu,  Yongchun Zhang,  Kaidi Chen,  Saleh Mobayen, 

Patch-based local deep feature extraction for automated skin cancer classification

Himanshu K. Gajera,  Mukesh A. Zaveri,  Deepak Ranjan Nayak, 

Att2ResNet: A deep attention-based approach for melanoma skin cancer classification

Said Yacine Boulahia,  Mohamed Akram Benatia,  Abderrahmane Bouzar, 
Free to Read

An ensemble model of convolution and recurrent neural network for skin disease classification

Belal Ahmad,  Mohd Usama,  Tanvir Ahmad,  Shabnam Khatoon,  Chaudhary Maqbool Alam, 

An optimal diagnosis system for melanoma dermoscopy images based on enhanced design of horse herd optimizer

Qi Ding,  Navid Razmjooy, 
Open Access

Handling dataset dependence with model ensembles for skin lesion classification from dermoscopic and clinical images

Ellák Somfai,  Benjámin Baffy,  Kristian Fenech,  Rita Hosszú,  Dorina Korózs,  Marcell Pólik,  Miklós Sárdy,  András Lőrincz, 

Dense and shuffle attention U-Net for automatic skin lesion segmentation

Guanzhong Zhang,  Shengsheng Wang, 

HS-UNET-ID: An approach for human skin classification integrating between UNET and improved dense convolutional network

Hai Thanh Nguyen,  Huong Hoang Luong,  Phat Tan Phan,  Hung Huy Duc Nguyen,  Duong Ly,  Duc Minh Phan,  Tin Trung Do, 

The effect of quantization at different resolutions on the classification of lesion texture in dermoscopic images using support vector machine

Doaa Mahmoud-Ghoneim, 

An all-inclusive computer-aided melanoma diagnosis based on soft computing

Xiongfei Jiao,  Juan Li,  Zhilei Zhao,  Benjamin Badami,