MINDS Team

Head : 

MINDS is a research group that conducts research activities in computational imaging and computer vision, with a main focus on:

  • Inverse problems applied to signal and image restoration, reconstruction, analysis and processing,
  • High resolution, high framerate imaging systems,
  • Dynamic imaging,
  • Machine learning applied to image processing and analysis

Computational imaging

MINDS research activities in computational imaging are centered on medical imaging, with a main focus on ultrasound. They concern the whole image formation and interpretation process including raw data acquisition by individual sensors using conventional and non-traditional sampling schemes, beamforming, image reconstruction, processing and analysis. The main research topics in computational ultrasound cover, but are not limited to:

  • Inverse problems: signal and image restoration, resolution enhancement, beamforming, compressed sensing, tissue motion estimation, flow velocity estimation
  • Linear and non-linear ultrasound imaging
  • Various clinical applications: oncology, cardiology, gynecology

MINDS also conducts research on other imaging modalities:

  • Computed tomography applied to endodontics
  • Multi-modal (ultrasound – magnetic resonance imaging) image registration and fusion applied to gynecology.

Computer vision

MINDS research activities in computer vision benefit from a broad range of expertise in camera calibration, stereo vision and motion analysis.

The main current research topics in computer vision include:

  • Still image analysis: interactive segmentation, over-segmentation, object identification;
  • Temporal image series: change detection, re-identification;
  • Video analysis: action recognition, scene reconstruction.

Applications concern:

  • Photographic landscape observatories;
  • Security: video analysis for criminal investigation, public transportation.

MINDS also considers other applications like fish ecology and astronomical image processing.

skills

Medical imaging
Computer vision
Inverse problems
High resolution fast imaging
Automatic learning for image
Landscape Observatories
IT security
Ultrasonic imaging
Sensor-medium modeling
Medical applications
Multi-physical and multimodal imaging

personnel of the team

publications of the team

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contrats of the team

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Friday 29 November 2019, 10h30
Compressive Sensing and Finite Rate of Innovation for Efficient Data Acquisition of Quantitative Acoustic Microscopy Images
Jong-Hoon KIM – Team MINDS, IRIT UT3 Paul Sabatier, IRIT, Auditorium J. Herbrand
#these
Thursday 19 September 2019, 10h00
Architectures d’apprentissage profond pour la reconnaissance d’actions humaines dans des séquences vidéo RGB-D monoculaires. Application à la surveillance dans les transports publics
Huy-Hieu PHAM – Team MINDS, IRIT UT3 Paul Sabatier, IRIT, Auditorium J. Herbrand
#these
Monday 1 July 2019, 10h30
Segmentation endodontique sur des images scanner 3D : méthodes et validation
Jérôme MICHETTI – Team MINDS, IRIT UT3 Paul Sabatier, IRIT, Auditorium J. Herbrand
#these
Friday 15 March 2019, 10h00
Estimation Parcimonieuse de Biais Multitrajets pour les Systèmes GNSS
Julien LESOUPLE – Team MINDS – IRIT INP-ENSEEIHT, Salle des thèses
#these
Tuesday 16 October 2018, 10h00
Cardiac Motion Estimation In Ultrasound Images using a Sparse Representation and Dictionary Learning
Nora Leïla OUZIR – Team MINDS – IRIT INP-ENSEEIHT, Salle des thèses
#these
Friday 25 November 2016, 15h30 – 17h00
Recent works on Compressed Ultrasound beamforming and brain connectivity analysis by diffusion MRI imaging at EPFL
  BESSON A., THIRAN J-P – Ecole Polytechnique Fédérale de Lausanne, LTS5 (Suisse) UT3 Paul Sabatier, IRIT, Salle 001
#seminaire