A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches
With the development of Computer-aided Diagnosis (CAD) and image scanning techniques,
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Whole-slide Image (WSI) scanners are widely used in the field of pathological diagnosis …
Efficient artificial intelligence approaches for medical image processing in healthcare: comprehensive review, taxonomy, and analysis
OAMF Alnaggar, BN Jagadale, MAN Saif… - Artificial Intelligence …, 2024 - Springer
In healthcare, medical practitioners employ various imaging techniques such as CT, X-ray,
PET, and MRI to diagnose patients, emphasizing the crucial need for early disease detection …
PET, and MRI to diagnose patients, emphasizing the crucial need for early disease detection …
A novel melanoma prediction model for imbalanced data using optimized SqueezeNet by bald eagle search optimization
Skin lesion classification plays a crucial role in diagnosing various gene and related local
medical cases in the field of dermoscopy. In this paper, a new model for the classification of …
medical cases in the field of dermoscopy. In this paper, a new model for the classification of …
Melanoma detection using deep learning-based classifications
One of the most prevalent cancers worldwide is skin cancer, and it is becoming more
common as the population ages. As a general rule, the earlier skin cancer can be …
common as the population ages. As a general rule, the earlier skin cancer can be …
A comparative study of deep learning architectures on melanoma detection
SH Kassani, PH Kassani - Tissue and Cell, 2019 - Elsevier
Melanoma is the most aggressive type of skin cancer, which significantly reduces the life
expectancy. Early detection of melanoma can reduce the morbidity and mortality associated …
expectancy. Early detection of melanoma can reduce the morbidity and mortality associated …
Classification of histopathological biopsy images using ensemble of deep learning networks
SH Kassani, PH Kassani, MJ Wesolowski… - arXiv preprint arXiv …, 2019 - arxiv.org
Breast cancer is one of the leading causes of death across the world in women. Early
diagnosis of this type of cancer is critical for treatment and patient care. Computer-aided …
diagnosis of this type of cancer is critical for treatment and patient care. Computer-aided …
Skin lesion classification based on deep convolutional neural networks architectures
J Saeed, S Zeebaree - Journal of Applied Science and Technology Trends, 2021 - jastt.org
Skin cancer is among the primary cancer types that manifest due to various dermatological
disorders, which may be further classified into several types based on morphological …
disorders, which may be further classified into several types based on morphological …
Diagnosing melanomas in Dermoscopy images using deep learning
When it comes to skin tumors and cancers, melanoma ranks among the most prevalent and
deadly. With the advancement of deep learning and computer vision, it is now possible to …
deadly. With the advancement of deep learning and computer vision, it is now possible to …
Construction of saliency map and hybrid set of features for efficient segmentation and classification of skin lesion
Skin cancer is being a most deadly type of cancers which have grown extensively worldwide
from the last decade. For an accurate detection and classification of melanoma, several …
from the last decade. For an accurate detection and classification of melanoma, several …
Breast cancer detection from biopsy images using nucleus guided transfer learning and belief based fusion
K George, S Faziludeen, P Sankaran - Computers in Biology and …, 2020 - Elsevier
Background and objective: Breast cancer is a frequently diagnosed cancer in women,
contributing to significant mortality rates. Death rates are relatively higher in developing …
contributing to significant mortality rates. Death rates are relatively higher in developing …