A review on smartphone skin cancer diagnosis apps in evaluation and benchmarking: coherent taxonomy, open issues and recommendation pathway solution
This research aims to review the attempts of researchers in response to the new and
disruptive technology of skin cancer applications in terms of evaluation and benchmarking …
disruptive technology of skin cancer applications in terms of evaluation and benchmarking …
An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach
Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the
annihilation in early stage implies a high survival rate therefore, it demands early diagnosis …
annihilation in early stage implies a high survival rate therefore, it demands early diagnosis …
Melanoma detection and classification using computerized analysis of dermoscopic systems: a review
Malignant melanoma is considered as one of the most deadly cancers, which has broadly
increased worldwide since the last decade. In 2018, around 91,270 cases of melanoma …
increased worldwide since the last decade. In 2018, around 91,270 cases of melanoma …
Combining deep learning and hand-crafted features for skin lesion classification
T Majtner, S Yildirim-Yayilgan… - 2016 Sixth International …, 2016 - ieeexplore.ieee.org
Melanoma is one of the most lethal forms of skin cancer. It occurs on the skin surface and
develops from cells known as melanocytes. The same cells are also responsible for benign …
develops from cells known as melanocytes. The same cells are also responsible for benign …
Melanoma skin cancer detection using a CNN-regularized extreme learning machine (RELM) based Model
Recent years have brought a heightened awareness of skin cancer as a potentially fatal type
of human disease. While all three forms of skin cancer—Melanoma, Basal, and Squamous …
of human disease. While all three forms of skin cancer—Melanoma, Basal, and Squamous …
A novel multi-task learning network for skin lesion classification based on multi-modal clues and label-level fusion
Q Lin, X Guo, B Feng, J Guo, S Ni, H Dong - Computers in Biology and …, 2024 - Elsevier
In this paper, we propose a multi-task learning (MTL) network based on the label-level
fusion of metadata and hand-crafted features by unsupervised clustering to generate new …
fusion of metadata and hand-crafted features by unsupervised clustering to generate new …
Optimised deep learning features for improved melanoma detection
T Majtner, S Yildirim-Yayilgan… - Multimedia Tools and …, 2019 - Springer
In this article, we are addressing the question of effective usage of the feature set extracted
from deep learning models pre-trained on ImageNet. Exploring this option will offer very fast …
from deep learning models pre-trained on ImageNet. Exploring this option will offer very fast …
A systematic review on smartphone skin cancer apps: coherent taxonomy, motivations, open challenges and recommendations, and new research direction
Objective: This research aims to survey the efforts of researchers in response to the new and
disruptive technology of skin cancer apps, map the research landscape from the literature …
disruptive technology of skin cancer apps, map the research landscape from the literature …
Pre-trained CNN based deep features with hand-crafted features and patient data for skin lesion classification
Skin cancer is a major public health problem, with millions newly diagnosed cases each
year. Melanoma is the deadliest form of skin cancer, responsible for the most over 6500 …
year. Melanoma is the deadliest form of skin cancer, responsible for the most over 6500 …
Improving skin lesion segmentation in dermoscopic images by thin artefacts removal methods
T Majtner, K Lidayova… - 2016 6th European …, 2016 - ieeexplore.ieee.org
In dermoscopic images, various thin artefacts naturally appear, most usually in the form of
hairs. While trying to find the border of the skin lesion, these artefacts effect the lesion …
hairs. While trying to find the border of the skin lesion, these artefacts effect the lesion …