[Matching of mammary microcalcifications on images from different views]. / Mise en correspondance de microcalcifications mammaires radiographiées sous différents angles.

PURPOSE: In order to increase sensitivity and specificity in the diagnosis of breast cancer, more than one - generally two or three - mammograms of the same breast are obtained. In order to be able to carry out 3D reconstruction of microcalcification clusters on one hand, and efficiently fuse the information they carry on the other hand, one needs to match corresponding regions of microcalcifications from the different views. Unfortunately, this may be difficult at times. To help the situation, we have developed in this paper, a technique to automatically match microcalcifications found on pairs of mammograms from the same breast. MATERIALS AND METHODS: We used the computed morphological characteristics of individual microcalcifications to build a likeness function to match the microcalcifications. The geometrical constraint suitable for the system used was then applied to reduce the possibilities. From the remaining possibilities, the one with the highest likeness was selected as pair of corresponding microcalcifications. RESULTS: This technique was tested on a number of real cases and yielded 77.14% of good matches. CONCLUSION: This technique provides good results and could therefore be used either directly or for 3D-reconstruction of clustered microcalcifications.

Towards a noninvasive intracranial tumor irradiation using 3d optical imaging and multimodal data registration.

Conformal radiotherapy (CRT) results in high-precision tumor volume irradiation. In fractioned radiotherapy (FRT), lesions are irradiated in several sessions so that healthy neighbouring tissues are better preserved than when treatment is carried out in one fraction. In the case of intracranial tumors, classical methods of patient positioning in the irradiation machine coordinate system are invasive and only allow for CRT in one irradiation session. This contribution presents a noninvasive positioning method representing a first step towards the combination of CRT and FRT. The 3D data used for the positioning is point clouds spread over the patient's head (CT-data usually acquired during treatment) and points distributed over the patient's face which are acquired with a structured light sensor fixed in the therapy room. The geometrical transformation linking the coordinate systems of the diagnosis device (CT-modality) and the 3D sensor of the therapy room (visible light modality) is obtained by registering the surfaces represented by the two 3D point sets. The geometrical relationship between the coordinate systems of the 3D sensor and the irradiation machine is given by a calibration of the sensor position in the therapy room. The global transformation, computed with the two previous transformations, is sufficient to predict the tumor position in the irradiation machine coordinate system with only the corresponding position in the CT-coordinate system. Results obtained for a phantom show that the mean positioning error of tumors on the treatment machine isocentre is 0.4 mm. Tests performed with human data proved that the registration algorithm is accurate (0.1 mm mean distance between homologous points) and robust even for facial expression changes.