INCISIVE is a 42-months research project, funded under the call DT-TDS-05-2020 – AI for Health Images.

The INCISIVE project aims to develop and validate a multimodal AI-based toolbox and an interoperable health imaging repository for the empowerment of imaging analysis related to the diagnosis, prediction and follow-up of cancer.

In its lifetime, INCISIVE will make use of multimodal data sources, including imaging, biological and Electronic Health Record (HER) to develop AI inference services for decision-support related to the management of cancer cases, as below:

For lung cancer:

• Chest X-rays classification
• CT scan segmentation
• PET/CT scan segmentation
• Cancer Staging
• 1-year metastasis risk prediction

For breast cancer:

• Mammography normal/suspicious classification
• Mammography Lesion Segmentation
• Mammography Breast density classification
• Mammography BIRADS classification

For prostate cancer:

• Instance Segmentation
• Lesion Segmentation
• ISUP Score Classification

For colorectal cancer:

• Lesion Segmentation
• Histopathological Image Analysis

For more information please visit https://incisive-project.eu/