SAMPL Clinical Research is the arm of SAMPL Lab at the Weizmann Institute of Science responsible for research collaborations with the medical community.

Medical Imaging is an essential tool for diagnosis and monitoring of patients. Yet despite its central role in modern medicine, it still faces some major challenges:

  •  As data acquisition is costly in terms of time, energy and physical space, imaging systems are often large and cumbersome, less accessible, and the imaging process can be lengthy and uncomfortable to patients
  •  Limited resolution due to physical constraints and loss of data during image formation
  •  Image interpretation by radiologists is naturally prone to variability and discordance
  •  In certain imaging modalities (ultrasound), the quality of image acquisition itself is very operator-dependent

SAMPL Clinical Research primary mission is to harness the innovative technologies developed at SAMPL lab – including advanced signal acquisition, processing and learning methods - for the purpose of making a positive impact on medicine, and medical imaging in particular. We facilitate the transition from pure theoretical research in the fields of signal processing and learning - to studies and solutions aiming to address real-world medical needs.

Some of our major topics of research include:

  •  Analysis of ultrasound “channel data” (the pre-processed form of data acquired in the memory of the ultrasound machine which is not in routine use), in attempt to enhance disease detection and assessment
  •  Use of multi-modality imaging and AI for earlier and better diagnosis of diseases
  •  Use of AI for conversion between imaging modalities (e.g., using deep learning to convert ultrasound images to CT images synthetically)
  •  AI-guided ultrasound image acquisition with the goal of overcoming operator-dependency
  •  Deep learning and contrast agents for super-resolution vascular ultrasound imaging
  •  Use of AI for Covid-19 diagnosis and prediction of outcome, in order to support the fight against the global pandemic
  •  Lung ultrasound
  •  Radar and other sensors for health applications