Semantic and object segmentation on photographic images of oral cancer

[Nature Portfolio] The official code for "A high-order focus interaction model and oral ulcer dataset for oral ulcer segmentation".

Repository for oral cancer photographic image classification

Towards explainable oral cancer recognition: Screening on imperfect images via Informed Deep Learning and Case-Based Reasoning

This repository accompanies the article entitled "Automated Classification of Oral Cancer Lesions: Vision Transformer vs Radiomics."

Deep learning workflow, that exploiting different models is able to classify and explain the classification

Model for early detection of Oral cancer via Histopathological Image datasets

Tool for Evaluating Deep Learning Models in Histopathological Image Analysis - A MATLAB-based User Interface [Tentative Version]

Oral Cancer diagnosis

Code for classification of cancerous vs. benign oral lesions using machine learning

This repository can be used to reproduce and/or update the tables and figures of our publication titled "Patterns of Lymph Node Involvement for Oral Cavity Squamous Cell Carcinoma".

Oral Cancer Classifier is an advanced image classification project focused on detecting oral cancer from histopathologic images. Leveraging the power of Convolutional Neural Networks (CNNs), this project transforms pixel-level data from oral tissue samples into actionable insights for early detection of cancer.