A Deep Learning-Based Automated Framework for Subpeak Designation on Intracranial Pressure Signals.

The intracranial pressure (ICP) signal, as monitored on patients in intensive care units, contains pulses of cardiac origin, where P1 and P2 subpeaks can often be observed. When calculable, the ratio of their relative amplitudes is an indicator of the patient's cerebral compliance. This characterization is particularly informative for the overall state of the cerebrospinal system.

Fusion of multiple segmentations of medical images using OVASSION and Deep Learning methods: Application to CT-Scans for tumoral kidney.

Nephroblastoma is the most common kidney tumour in children. Its diagnosis is based on imagery. In the SAIAD project, we have designed a platform for optimizing the segmentation of deformed kidney and tumour with a small dataset, using Artificial Intelligence methods.

Conflict management in the fusion of complementary segmentations of deformed kidneys and nephroblastoma.

The fusion of multiple segmentations aims to improve their accuracy in order to make them exploitable. However, conflicts may appear. In this paper, two conflict-management models are proposed for the fusion of complementary segmentations.