Objectives & outcomes:
- AI/ML-driven accurate segmentation and prediction models
- Explainable AI for transparent model predictions
- Breast cancer subtype prediction (Luminal A, Luminal B, HER2, TNBC)
- Breast cancer hormone receptor status prediction (ER, PR, HER2, Triple Negative)
- Automated Tumor and vessel segmentation for Breast MRI Images
- Brain Glioblastoma Tumor Segmentation and MGMT Status prediction
Salient features:
- Radiologist feedback to improve the model segmentation
- A robust pipeline adaptable to other solid tumors and imaging modalities (MRI, CT, Mammograms)
- Brain integration for glioblastoma analysis
Demo use case: Breast cancer subtyping
Data source: Duke MRI Breast Cancer Dataset
Business model: Contract services
Please write to us:
for details & we will be happy to discuss: ramscanbd@citadelpm.io