Christophe Lohou

Interactive 3D segmentation by tubular envelope model for the aorta treatment

We propose a novel interactive 3D segmentation approach and geometric model definition called tubular envelope model. It is conceived to express the shape of tubular objects. The main challenges we have achieved are the speed and interactivity of the construction. A computer program designed for this task gives the user full control of the shape and precision, with no significant computational errors. Six CT (computed tomography) aortic dissection images have been used for the tubular envelopes construction. Hence, we have proposed a generic parametric model of the aorta for its interactive construction. It leads us to rapid visualization and navigation inside the artery (rough virtual angioscopy). The low complexity of the model and the ease of interactive design makes the tubular envelope suitable for aorta segmentation in comparison to the other segmentation methods. The model accuracy is adjustable by the user according to his requirements; the time of construction is approved by clinicians. More generally, the tubular envelope could be used in other applications, e.g. to define a region of interest for more precise segmentation or feature extraction inside, to develop a parametric model with deformation capabilities.

3D segmentation of the true and false lumens on CT aortic dissection images

Our works are related to aortic dissections which are a medical emergency and can quickly lead to death. In this paper, we want to retrieve in CT images the false and the true lumens which are aortic dissection features. Our aim is to provide a 3D view of the lumens that we can difficultly obtain either by volume rendering or by another visualization tool which only directly gives the outer contour of the aorta; or by other segmentation methods because they mainly directly segment either only the outer contour of the aorta or other connected arteries and organs both. In our work, we need to segment the two lumens separately; this segmentation will allow us to: distinguish them automatically, facilitate the landing of the aortic prosthesis, propose a virtual 3d navigation and do quantitative analysis. We chose to segment these data by using a deformable model based on the fast marching method. In the classical fast marching approach, a speed function is used to control the front propagation of a deforming curve. The speed function is only based on the image gradient. In our CT images, due to the low resolution, with the fast marching the front propagates from a lumen to the other; therefore, the gradient data is insufficient to have accurate segmentation results. In the paper, we have adapted the fast marching method more particularly by modifying the speed function and we succeed in segmenting the two lumens separately.

Automatic calibration of a single-projector catadioptric display system

We describe the calibration of a catadioptric omnidirectional video projection system that adjusts its projection to the geometry of any scene by means of a rotating camera. Correction of geometric distortions requires 3D reconstruction of the scene. A camera is used to detect projected point features and calibration is performed in three successive steps: precalibration of camera assuming pure rotation, precalibration of catadioptric projector under central approximation and calibration of the global system, by minimizing the squared distance between the reflected and perceived rays, and by relaxing previous constraints, to refine values of extrinsic parameters. Simulation is used to validate estimated values of parameters and distance between the 3D reconstruction of the projection room and its expected geometry. Influence of noise in detected point coordinates is studied and preliminary results for the reconstruction and projection in real conditions are reported.

3D/2D image registration by image transformation descriptors (ITDs) for thoracic aorta imaging

In this article, we present a novel image registration technique. Unlike most state of the art methods, our approach allows us to compute directly the relationship between images. The proposed registration framework, built in a modular way, can be adjusted to particular problems. Tests on sample image database of thoracic aorta proved that our method is fast and robust and could be successfully used for many cases. We have enhanced our previous works to provide a rapid 3D/2D registration method. It uses direct computing of the image transformation descriptors (ITDs) to align the projection images. The 3D transformation is estimated by an interesting technique which allows to propose a 3D pose update, interpreting the 2D transform of the projections in the 3D domain. The presented 3D/2D registration technique based on ITDs can be used as an initialization technique for classic registration algorithms. Its unique properties can be advantageous for many image alignment problems. The possibility of using different descriptors, adapted for particular cases, makes our approach very flexible. Fast time of computing is an important feature and motivates to use our technique even as an initialization step before execution of well known standard algorithms which could be more precise, but slow and sensitive to initialization of the parameters.

Detection of the aortic intimal tears by using 3D digital topology

Aortic dissection is a real problem of public health, it is a medical emergency and may quickly lead to death. Aortic dissection is caused by aortal tissue perforation because of blood pressure. It consists of tears (or holes of the intimal tissue) inside lumens. These tears are difficult to detect because they do not correspond to a filled organ to segment; they are usually visually retrieved by radiologists by examining gray level variation on successive image slices, but it remains a very difficult and error-prone task. Our purpose is to detect these intimal tears to help cardiac surgeons in making diagnosis. It would be useful either during a preoperative phase (visualization and location of tears, endoprothesis sizing); or during a peroperative phase (a registration of tears on angiographic images would lead to a more accuracy of surgeons gestures and thus would enhance care of patient). At this aim, we use Aktouf et al.s holes filling algorithm proposed in the field of digital topology. This algorithm permits the filling of holes of a 3D binary object by using topological notions - the holes are precisely the intimal tears for our aortic dissection images, after a first preprocessing step. As far as we know, this is the first time that such a proposal is made, even if it is a crucial data for cardiac surgeons. Our study is a preliminary and innovative work; our results are nevertheless considered satisfactory. This approach would also gain to be known to specialists of other diseases.

A non-iterative registration method based on image transformation descriptors

In this article we present a novel method of the image registration based on the image transformation descriptors which are also introduced in this paper. The algorithm computes the registration parameters directly, on the contrary to the most known, iterative methods. It is fast and robust and therefore can be used as an initialization for the more accurate (but slower) algorithms. Our registration technique relies on the values obtained from appropriate transformation descriptions (image transformation descriptors, ITDs), computed from the geometric properties present on the images. It is also possible to adapt the process to a specific registration problem by providing custom descriptors, specific for a particular case. To prove the usability of the method, we have successfully tested it for registering 3D CT images with the angiography of thoracic aortas.

Augmented digitally reconstructed radiographs of aortic dissection CTA images

To deal with aortic dissections, physicians require preoperative 3D Computed Tomography Angiography - or CTA - images, then intraoperative 2D fluoroscopic X-ray angiographic images. In one hand, only the injected contrast agent/X-rays combination allows physicians to detect aortas contour, but it remains very difficult to obtain the adequate acquisition parameters. In another hand, the Digitally Reconstructed Radiograph method allows us to obtain a simulated rendering of a CTA with a fluoroscopic shading, but due to aortas tissue, the aorta is not visible. In a recent study, we have proposed an interactive segmentation of aortic dissection CTA images which produces a tubular envelope wrapping aortas wall. In this study, by computing and simply overlapping both Digitally Reconstructed Radiographs of the initial CTA image and of its corresponding tubular envelope image, we easily obtain a 2D view - called Augmented Digitally Reconstructed Radiograph - that makes aorta visible. Thus, such a preoperative work gives physicians a synthesis view the most similar possible to the one acquired during intervention, but with additional features (aortas contour, aortic dissection features ...). This work will be used to automatically propose the best acquisition parameters, for aortic prostheses implantation.