Medical Image Analysis

When I joined the GMCAO research group at TIMC laboratory in 2006, I contributed my expertise in medical image processing and analysis to three ongoing applied projects led by my colleagues. These collaborations allowed me to tackle diverse clinical challenges — from real-time surgical vision to oncological dose computation — while immersing myself in the tools and culture of the team.

These three projects are grounded in rigorous academic knowledge production: each contribution led to publications in international peer-reviewed journals and conferences, or to a patent filing. The skills described here were forged alongside that scientific output — they are its direct product.

These three projects embody a conviction that has shaped my entire approach: a medical image is only as good as its usability by the clinician, at the right moment and in the right context.

Prostate Brachytherapy — Orientation of Iodine-125 Seeds

Project led by Jocelyne Troccaz (TIMC-GMCAO)
Co-supervision of post-doctoral researcher Giao Nguyen (50%, with Jocelyne Troccaz)

Context

Prostate brachytherapy involves implanting radioactive iodine-125 seeds directly into the prostate gland. Calculating the radiation dose absorbed by tumour tissue — dosimetry — is critical for evaluating treatment effectiveness and anticipating side effects. At the time, dosimetry tools modelled seeds as isotropic point sources, ignoring their actual orientation within the tissue.

The research question: does seed orientation influence dosimetry enough to warrant its inclusion in clinical software?

Contributions

To answer this, we first needed to automatically detect and localise seeds in post-operative CT images — a challenging task, as seeds are small, closely spaced, and may overlap in projection.

We developed a complete pipeline for:

• Segmentation of iodine seeds in CT images
• Separation of seeds that touch or overlap
• Pose estimation (3D position + orientation) of each individual seed

Results confirmed that seed orientation had a measurable impact on dosimetry — a clinically significant finding for post-operative evaluation and treatment follow-up.

Skills Applied

• 3D medical image processing (CT)
• Geometric modelling of radioactive sources
• Software development and integration into the CamiTK platform for clinical use
• Validation protocols on real patient data

Related Publications

• [IEEE TBME 2015] H.-G. Nguyen, C. Fouard, J. Troccaz — Segmentation, separation and pose estimation of prostate brachytherapy seeds in CT images — read
• [Cancer/Radiothérapie 2014] F. Meneu, H. Nguyen, C. Fouard et al. — Impact de l’orientation des grains iode 125 dans l’évaluation de la dosimétrie à 1 mois — read
• [Physica Medica 2013] F. Meneu, G. Nguyen et al. — Consideration of seeds orientation in prostate brachytherapy and dosimetry analysis — read

3D Ultrasound-Based Bone Tracking

Co-supervision at 50%, with Jocelyne Troccaz
PhD thesis of Jonathan Schers (2006–2009)

Context

Orthopaedic procedures — prosthesis placement, osteotomies — require real-time tracking of bone structures during surgery. Classical techniques rely either on X-ray imaging (radiation) or on invasive bone markers. The goal of this project was to explore a minimally invasive alternative: tracking bone structures using 3D ultrasound.

Contributions

We proposed a per-operative tracking method based on 3D/3D ultrasound image registration: from a reference volume acquired at the start of the procedure, bone displacements are tracked by registering each new acquisition against that reference.

Key scientific contributions:

• Segmentation of bone surfaces in ultrasound images (noisy signal, reflection artefacts)
• Rigid and deformable registration methods adapted to the ultrasound modality
• Panoramic reconstruction from multiple partial acquisitions
• Evaluation on cadaveric anatomical specimens

Skills Applied

• Ultrasound signal processing
• Multimodal medical image registration
• Design of a ground-truth-free registration validation method
• Doctoral co-supervision (50%)

Related Publications

• [IUS 1007] J. Schers, J. Troccaz, V. Daanen, C. Fouard, C. Plaskos, P. Kilian - 3D/4D ultrasound registration of bone - read
• [IJCARS 2009] J. Schers, J. Troccaz, C. Fouard, C. Plaskos, O. Palombi — 3D/3D ultrasound registration for panoramic volume reconstruction — read
• [CAOS 2010] J. Schers, C. Fouard, J. Troccaz — Non invasive ultrasound-based bone tracking — read

Distributed Laparoscopy — Extended View of the Surgical Field

Co-supervision at 50%, with Philippe Cinquin
PhD thesis of Christophe Boschet (2007–2010)

Context

During a laparoscopic procedure, the surgeon’s field of view is very narrow: the endoscopic camera, inserted through a trocar, only covers a small portion of the abdominal cavity. The surgeon must constantly reposition the camera to explore the operative field, which is cognitively demanding and lengthens procedures.

The idea: replace a single high-resolution camera with several small, distributed miniature cameras (similar to the phone cameras of the day), and reconstruct a real-time 3D panoramic view of the operative zone.

Contributions

This project posed novel challenges at the intersection of computer vision and embedded computing:

• Calibration of multiple miniature cameras in an endoscopic configuration
• 3D reconstruction of the surgical field via distributed stereovision
• Fusion of video streams to produce a coherent augmented view
• Integration into the CamiTK platform and prototyping for pre-clinical experimentation

The project remained at the research prototype stage but led to a European patent filing.

Skills Applied

• Stereoscopic computer vision
• Multi-camera optical system calibration
• Hardware/software integration
• Patent writing

Related Output

• [Patent EP 2016] P. Cinquin, S. Voros, C. Boschet, C. Fouard, A. Moreau-Gaudry — Imaging system for the three dimensional observation of an operation field — read

What These Projects Taught Me

These three collaborations were a practical school in medical prototyping — and far more than a checklist of technical skills.

I learned to work with real, imperfect clinical data, often without ground truth available to validate the algorithms. I developed the reflex of designing rigorous evaluation protocols where standard benchmarks didn’t exist, and of integrating operating room constraints from the design phase — time pressure, sterility requirements, ergonomics for the surgeon.

I also shaped my collaborative approach: learning to ask the right questions to clinicians, to translate a medical need into an algorithmic problem, to deliver tools integrated into a software platform usable by non-computer-scientists.

These skills — built alongside a sustained effort in scientific publication and formal knowledge production — are the ones I bring today to medical application prototyping.