A5034167853- Medical Imaging Techniques and Applications
- Machine Learning in Healthcare
- Radiomics and Machine Learning in Medical Imaging
- Artificial Intelligence in Healthcare and Education
- Cell Image Analysis Techniques
- Advanced X-ray and CT Imaging
- Anomaly Detection Techniques and Applications
- Advanced Semiconductor Detectors and Materials
- Generative Adversarial Networks and Image Synthesis
- Air Quality Monitoring and Forecasting
- Advanced Radiotherapy Techniques
- Air Traffic Management and Optimization
- Atmospheric aerosols and clouds
- AI in cancer detection
- Radiation Detection and Scintillator Technologies
Pitié-Salpêtrière Hospital
2024
Sorbonne Université
2024
Centre National de la Recherche Scientifique
2024
Assistance Publique – Hôpitaux de Paris
2024
Institut du Cerveau
2024
Inserm
2024
Unsupervised anomaly detection is a popular approach for the analysis of neuroimaging data as it allows identifying wide variety anomalies from unlabelled data. It relies on reconstructing subject-specific model healthy appearance to which subject's image can be compared detect anomalies. In literature, common rely analysing residual between real and its pseudo-healthy reconstruction. This however has limitations partly due reconstructions being imperfect lack natural thresholding mechanism....
Over the past years, pseudo-healthy reconstruction for unsupervised anomaly detection has gained in popularity. This approach great advantage of not requiring tedious pixel-wise data annotation and offers possibility to generalize any kind anomalies, including that corresponding rare diseases. By training a deep generative model with only images from healthy subjects, will learn reconstruct images. is then compared input detect localize anomalies. The evaluation such methods often relies on...
Medical imaging is spearheading the AI transformation of healthcare. Performance reporting key to determine which methods should be translated into clinical practice. Frequently, broad conclusions are simply derived from mean performance values. In this paper, we argue that common practice often a misleading simplification as it ignores variability. Our contribution threefold. (1) Analyzing all MICCAI segmentation papers (n = 221) published in 2023, first observe more than 50% do not assess...
The growing interest of cancer surgeons for intra-operative probes has led to the development several prototypes high resolution mini gamma cameras. aim this paper is present a global characterization one authors developed and corresponding first evaluation in clinical context. current prototype POCI (peroperative compact imager) 24 mm diameter intensified position sensitive diode. In order face various situations, two sets collimator/scintillator imaging head have been either spatial or...
Aerosol-cloud interactions (ACI) include various effects that result from aerosols entering a cloud, and affecting cloud properties. In general, an increase in aerosol concentration results smaller droplet sizes which leads to larger, brighter, longer-lasting clouds reflect more sunlight cool the Earth. The strength of effect is however heterogeneous, meaning it depends on surrounding environment, making ACI one most uncertain our current climate models. work, we use causal machine learning...
Unsupervised anomaly detection is a popular approach for the analysis of neuroimaging data as it allows to identify wide variety anomalies from unlabelled data. It relies on building subject-specific model healthy appearance which subject's image can be compared detect anomalies. In literature, common rely analysing residual between and its pseudo-healthy reconstruction. This however has limitations partly due reconstructions being imperfect lack natural thresholding mechanism. Our proposed...
The development of a hand-held /spl gamma/-imaging probe for inside body localization small tumors is first interest radio-guided operative cancer surgery. In that context, the authors have developed sub-millimeter spatial resolution, field view, gamma/-per-operative compact imager (POCI). It consists head module composed high resolution tungsten collimator and YAP:Ce crystal plate, optically coupled to an intensified position sensitive diode (IPSD). report here essential imaging...