Medical image segmentation using deep semantic-based methods: A review of techniques, applications and emerging trends
Semantic-based segmentation (Semseg) methods play an essential part in medical imaging
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is …
[HTML][HTML] A survey, review, and future trends of skin lesion segmentation and classification
Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …
analysis is an emerging field of research that has the potential to alleviate the burden and …
FAT-Net: Feature adaptive transformers for automated skin lesion segmentation
Skin lesion segmentation from dermoscopic image is essential for improving the quantitative
analysis of melanoma. However, it is still a challenging task due to the large scale variations …
analysis of melanoma. However, it is still a challenging task due to the large scale variations …
Multiclass skin lesion classification using hybrid deep features selection and extreme learning machine
The variation in skin textures and injuries, as well as the detection and classification of skin
cancer, is a difficult task. Manually detecting skin lesions from dermoscopy images is a …
cancer, is a difficult task. Manually detecting skin lesions from dermoscopy images is a …
A survey on deep learning for skin lesion segmentation
Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …
Skin lesion extraction using multiscale morphological local variance reconstruction based watershed transform and fast fuzzy C-means clustering
Early identification of melanocytic skin lesions increases the survival rate for skin cancer
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …
patients. Automated melanocytic skin lesion extraction from dermoscopic images using the …
FF-UNet: a U-shaped deep convolutional neural network for multimodal biomedical image segmentation
Automatic multimodal image segmentation is considered a challenging research area in the
biomedical field. U-shaped models have led to an enormous breakthrough in a large …
biomedical field. U-shaped models have led to an enormous breakthrough in a large …
A hierarchical three-step superpixels and deep learning framework for skin lesion classification
Skin cancer is one of the most common and dangerous cancer that exists worldwide.
Malignant melanoma is one of the most dangerous skin cancer types has a high mortality …
Malignant melanoma is one of the most dangerous skin cancer types has a high mortality …
Comparison of the impacts of dermoscopy image augmentation methods on skin cancer classification and a new augmentation method with wavelet packets
E Goceri - International Journal of Imaging Systems and …, 2023 - Wiley Online Library
This work aims to determine the most suitable technique for dermoscopy image
augmentation to improve the performance of lesion classifications. Also, a new …
augmentation to improve the performance of lesion classifications. Also, a new …
Intra-class consistency and inter-class discrimination feature learning for automatic skin lesion classification
Automated skin lesion classification has been proved to be capable of improving the
diagnostic performance for dermoscopic images. Although many successes have been …
diagnostic performance for dermoscopic images. Although many successes have been …