Pilot on Remote AutomatiC ulTrasound scan analysIs for hemophiliC patiEnts
Introduction to the pilot
Currently, hemophilic patients need to frequently visit specialized centers, but this is not always possible, for example due to the distance from the center. The project aims to offer a convenient diagnostic procedure that is user-friendly, enabling patients to receive prompt and accurate diagnoses without the necessity of physically attending specialized centers. This approach will help minimize the risks of under or over-treatment, thus providing an added advantage to patients’ overall well-being.
The patient or caregiver can acquire ultrasound images at home using a portable ultrasound probe connected to a mobile PC. However, acquiring high-quality ultrasound images can be challenging and often requires extensive training. To simplify the process for patients or caregivers, we are developing the GAJA app, which leverages machine learning models to provide guidance during the image acquisition process.
Once the practitioners receive the acquired images, their role is to provide a diagnosis. To expedite the procedure and enhance diagnostic accuracy, we are developing CADET, a specialized computer-aided diagnosis tool. CADET leverages advanced machine learning models to prioritize interventions and intelligently reorganize the received images. Additionally, CADET autonomously identifies conditions like joint distention, providing valuable assistance to practitioners during the diagnostic process.
GAJA - Guided self-Acquisition of Joint ultrAsound images, International Workshop on Advances in Simplifying Medical Ultrasound (ASMUS 2023 (MICCAI Workshop)), 2023 Publication
A Computer-Aided Diagnosis Tool for the Detection of Hemarthrosis By Remote Joint Ultrasound in Patients with Hemophilia, Blood, 140(Supplement 1), 464-465., 2022 Publication
Ultrasound Detection of Subquadricipital Recess Distension, Intelligent Systems with Applications, 200183., 2023 Publication