Melanoma lesion detection and segmentation using deep region based convolutional neural network and fuzzy C-means clustering
Objective Melanoma is a dangerous form of the skin cancer responsible for thousands of
deaths every year. Early detection of melanoma is possible through visual inspection of …
deaths every year. Early detection of melanoma is possible through visual inspection of …
Skin cancer detection from dermoscopic images using deep learning and fuzzy k‐means clustering
Melanoma skin cancer is the most life‐threatening and fatal disease among the family of
skin cancer diseases. Modern technological developments and research methodologies …
skin cancer diseases. Modern technological developments and research methodologies …
Hybrid fully convolutional networks‐based skin lesion segmentation and melanoma detection using deep feature
K Jayapriya, IJ Jacob - International Journal of Imaging …, 2020 - Wiley Online Library
Fully convolutional networks (FCNs) take the input of arbitrary size and produce
correspondingly sized output with efficient inference and learning. The automatic diagnosis …
correspondingly sized output with efficient inference and learning. The automatic diagnosis …
Melanoma segmentation: A framework of improved DenseNet77 and UNET convolutional neural network
Melanoma is the most fatal type of skin cancer which can cause the death of victims at the
advanced stage. Extensive work has been presented by the researcher on computer vision …
advanced stage. Extensive work has been presented by the researcher on computer vision …
[HTML][HTML] Automatic lesion segmentation using atrous convolutional deep neural networks in dermoscopic skin cancer images
Background Melanoma is the most dangerous and aggressive form among skin cancers,
exhibiting a high mortality rate worldwide. Biopsy and histopathological analysis are …
exhibiting a high mortality rate worldwide. Biopsy and histopathological analysis are …
Automatic segmentation of melanoma skin cancer using transfer learning and fine-tuning
The massive use of multimedia technologies has enabled the exploration of information in
many data such as texts, audio, videos, and images. Computational methods are being …
many data such as texts, audio, videos, and images. Computational methods are being …
Automatic skin lesion segmentation and melanoma detection: Transfer learning approach with u-net and dcnn-svm
Industrial pollution resulting in ozone layer depletion has influenced increased UV radiation
in recent years which is a major environmental risk factor for invasive skin cancer …
in recent years which is a major environmental risk factor for invasive skin cancer …
[HTML][HTML] Skin lesion analysis for melanoma detection using the novel deep learning model fuzzy GC-SCNN
U Bhimavarapu, G Battineni - Healthcare, 2022 - mdpi.com
Melanoma is easily detectable by visual examination since it occurs on the skin's surface. In
melanomas, which are the most severe types of skin cancer, the cells that make melanin are …
melanomas, which are the most severe types of skin cancer, the cells that make melanin are …
Melanoma localization and classification through faster region-based convolutional neural network and SVM
Melanoma is a lethal skin cancer disease affecting millions of people around the globe and
has a high mortality rate. Dermatologists perform the manual inspection through visual …
has a high mortality rate. Dermatologists perform the manual inspection through visual …
Skin lesion segmentation based on improved u-net
Melanoma is one of the most common and dangerous skin cancers, accounting for 75% of
deaths associated with skin cancer. Detection of melanoma in early stages can significantly …
deaths associated with skin cancer. Detection of melanoma in early stages can significantly …