Hierarchical probabilistic 3D U-Net, with attention mechanisms (—𝘈𝘵𝘵𝘦𝘯𝘵𝘪𝘰𝘯 𝘜-𝘕𝘦𝘵, 𝘚𝘌𝘙𝘦𝘴𝘕𝘦𝘵) and a nested decoder structure with deep supervision (—𝘜𝘕𝘦𝘵++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Computer-assisted image straightening and cropping
Official Python implementation of IEEE JBHI 2021 paper: "Choquet Integral and Coalition Game-based Ensemble of Deep Learning Models for COVID-19 Screening from Chest X-ray Images"
📎 About MIMBCD-UI Project
Computer-aided detection and diagnosis program
AiAi code-charity project for Cancer and Tuberculosis screening in Radiology Chest X-Rays (PA - CXR) using Deep Learning powered CAD algorithms. Come join our all-volunteer team to improve the healthcare in emerging nations!
C++ implementation of oral cancer detection on CT images
Análisis Computacional de Eventos de Protesta (ACEP). Computer-Aided Protest Event Analysis (CAPEA)
Clinically Significant Prostate Cancer Detection in bpMRI using models trained with Report Guided Annotations
📎 About BreastScreening Project
Public release of ProstAttention-Net: A deep attention model for prostate cancer segmentation by aggressiveness in MRI scans
🌐 MIDA Project Webpage
🍬 Low-Fidelity Prototypes
The open source code for the paper "A Hybrid Multi-stage Model based on YOLO and Modified Inception Network for Rice Leaf Disease Analysis" Hybrid_Multi_Stage_DeepLearing_Approach
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