Polarized 3D Endoscopy
The project aims to enhance deep learning for medical imaging by integrating intelligent optical methods to improve diagnosis accuracy and treatment efficiency.
Projectdetails
Introduction
The proliferation of artificial intelligence (AI) has led to a major advancement in many fields. It has enabled achieving non-precedent achievements such as human-level image recognition, intelligible language translation, and accurate medical diagnosis.
Research Goals
The main research goal of the PI’s ERC-StG SPADE project is to use tools for data modelling to improve our understanding and usage of deep learning (DL) and thus enhance its performance in medical problems and computational imaging [1-4].
Potential Benefits
One of the fields that could greatly benefit from such progress is sensitive medical treatment, using AI-based medical devices. Such devices can initially assist the physicians with a more accurate diagnosis and potentially save lives.
As such technology matures, the information provided to the physicians will be richer, thus leading to more accurate diagnoses to the cases at hand. Such advancement will allow high quality and efficient treatment to a much wider public.
Project Scope
The scope of this POC is to apply intelligent optical imaging methods developed in the SPADE project, specifically for introducing reliable 3D and polarization information to medical imaging devices.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 150.000 |
Totale projectbegroting | € 150.000 |
Tijdlijn
Startdatum | 1-10-2023 |
Einddatum | 30-9-2025 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- TEL AVIV UNIVERSITYpenvoerder
Land(en)
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STED-enabled super-resolution multimode-fibre based holographic endoscopy for deep-tissue observations of neuronal connectivity
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