Use of artificial intelligence in diagnosis of head and neck precancerous and cancerous lesions: a systematic review
This systematic review analyses and describes the application and diagnostic accuracy of
Artificial Intelligence (AI) methods used for detection and grading of potentially malignant …
Artificial Intelligence (AI) methods used for detection and grading of potentially malignant …
AI-based carcinoma detection and classification using histopathological images: A systematic review
Histopathological image analysis is the gold standard to diagnose cancer. Carcinoma is a
subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell …
subtype of cancer that constitutes more than 80% of all cancer cases. Squamous cell …
Efficient deep learning model for mitosis detection using breast histopathology images
Mitosis detection is one of the critical factors of cancer prognosis, carrying significant
diagnostic information required for breast cancer grading. It provides vital clues to estimate …
diagnostic information required for breast cancer grading. It provides vital clues to estimate …
Evolutionary algorithm based classifier parameter tuning for automatic diabetic retinopathy grading: A hybrid feature extraction approach
Human eye is one of the most sophisticated organ, with retina, pupil, iris cornea, lens and
optic nerve. Automatic retinal image analysis is emerging as an important screening tool for …
optic nerve. Automatic retinal image analysis is emerging as an important screening tool for …
Automatic identification of clinically relevant regions from oral tissue histological images for oral squamous cell carcinoma diagnosis
DK Das, S Bose, AK Maiti, B Mitra, G Mukherjee… - Tissue and Cell, 2018 - Elsevier
Identification of various constituent layers such as epithelial, subepithelial, and keratin of
oral mucosa and characterization of keratin pearls within keratin region as well, are the …
oral mucosa and characterization of keratin pearls within keratin region as well, are the …
Automated oral squamous cell carcinoma identification using shape, texture and color features of whole image strips
Despite profound knowledge of the incidence of oral cancers and a large body of research
beyond it, it continues to beat diagnosis and treatment management. Post physical …
beyond it, it continues to beat diagnosis and treatment management. Post physical …
Machine learning concepts applied to oral pathology and oral medicine: a convolutional neural networks' approach
ALD Araújo, VM da Silva, MS Kudo… - Journal of Oral …, 2023 - Wiley Online Library
Introduction Artificial intelligence models and networks can learn and process dense
information in a short time, leading to an efficient, objective, and accurate clinical and …
information in a short time, leading to an efficient, objective, and accurate clinical and …
Computational analysis of histological images from hematoxylin and eosin-stained oral epithelial dysplasia tissue sections
Oral epithelial dysplasia is a precancerous lesion that presents alterations in the shape and
size of cell nuclei and can be graded as mild, moderate and severe. The conventional …
size of cell nuclei and can be graded as mild, moderate and severe. The conventional …
Automated oral cancer identification using histopathological images: a hybrid feature extraction paradigm
Oral cancer (OC) is the sixth most common cancer in the world. In India it is the most
common malignant neoplasm. Histopathological images have widely been used in the …
common malignant neoplasm. Histopathological images have widely been used in the …
Aquila-particle swarm based cooperative search optimizer with superpixel techniques for epithelial layer segmentation
The segmentation of epithelial layers from oral histopathology images plays a crucial role for
early detection of oral cancer disease. As a result, more accurate segmentation of this layer …
early detection of oral cancer disease. As a result, more accurate segmentation of this layer …