Paolo Campodonico

ORCID: 0000-0002-4532-9657
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About
Contact & Profiles
Research Areas
  • Medical Imaging Techniques and Applications
  • Sparse and Compressive Sensing Techniques
  • Advanced X-ray and CT Imaging
  • Cognitive Science and Mapping
  • Thermography and Photoacoustic Techniques
  • Ultrasound and Hyperthermia Applications
  • Photoacoustic and Ultrasonic Imaging

University of Cambridge
2021

Photoacoustic tomography (PAT) is an emerging imaging modality that aims at measuring the high-contrast optical properties of tissues by means high-resolution ultrasonic measurements. The interaction between these two types waves based on thermoacoustic effect. In recent years, many works have investigated applicability compressed sensing to PAT in order reduce times while maintaining a high reconstruction quality. However, most cases, theoretical guarantees are missing. this work, we show...

10.1137/20m1375152 article EN SIAM Journal on Imaging Sciences 2021-01-01

We introduce the Consistent Reasoning Paradox (CRP). reasoning, which lies at core of human intelligence, is ability to handle tasks that are equivalent, yet described by different sentences ('Tell me time!' and 'What time?'). The CRP asserts consistent reasoning implies fallibility -- in particular, human-like intelligence AI necessarily comes with fallibility. Specifically, it states there problems, e.g. basic arithmetic, where any always answers strives mimic consistently will hallucinate...

10.48550/arxiv.2408.02357 preprint EN arXiv (Cornell University) 2024-08-05

Undersampled inverse problems occur everywhere in the sciences including medical imaging, radar, astronomy etc., yielding underdetermined linear or non-linear reconstruction problems. There are now a myriad of techniques to design decoders that can tackle such problems, ranging from optimization based approaches, as compressed sensing, deep learning (DL), and variants between two techniques. The variety methods begs for unifying approach determine existence optimal fundamental accuracy...

10.48550/arxiv.2311.16898 preprint EN public-domain arXiv (Cornell University) 2023-01-01
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