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Special Issue on biomedical image segmentation using variational and statistical approaches
| Content Provider | Semantic Scholar |
|---|---|
| Author | Cohen, Laurent D. Djemal, Khalifa Ruan, Su Toumoulin, Christine |
| Copyright Year | 2014 |
| Abstract | g 3 o r Technological advances in medical imaging have been xtremely fast over the last decades, making human observaion possible at different scales from molecular to cellular to rgan even the whole body. According to the modality, imaging s able to furnish morphological, structural, metabolic and funcional information, which can be conjointly exploited to improve he understanding of the disease and assist the medical expert n the decision-making. As a consequence, usage of medical maging has greatly increased to play today a key role in clincal practice in all phases of the management of the disease. hese include prediction, diagnosis, therapy planning, therapy uidance, intervention guidance, monitoring. . . However, a major challenge is how to deal with the big mount of available data, interpret and exploit them in order o really bring a valuable help to medical experts whether in he decision-making or for improving the procedure safety and utcome. To deal with the technological problems of image analyis, computer aided systems have been developing for advanced pplications dedicated to image guided diagnosis (CAD), therpy and intervention, including planning treatment. However, he complexity of image content, their size and their number mpose to design processing tools that meet the clinical requireents (accuracy, robustness, and computation time). Among hese tools, the segmentation appears as a prerequisite and a ey step for all these applications. A lot of work have been evoted to this segmentation and continue to be developed. espite advances in the mathematical tools as well in the image esolution, segmentation still remains an open problem. The hallenges of medical image segmentation are often related to he low contrast, the presence of noise and different kinds of rtefacts (presence of extrinsic objects, motion. . .) but also to he shape complexity of the structure of interest, its contrast and eometry variability over time or in the course of the treatment, nd the tissue environment into which this structure stands. This issue includes a special session on the segmentation tage. It came out after a workshop on image segmentation, hich was jointly organized by the GdR ISIS (CNRS structure or animation of research on Information, Signal, Image, ViSion) nd the GdR STIC Santé (CNRS and INSERM structure for w p a |
| Starting Page | 1 |
| Ending Page | 2 |
| Page Count | 2 |
| File Format | PDF HTM / HTML |
| DOI | 10.1016/j.irbm.2014.02.001 |
| Volume Number | 35 |
| Alternate Webpage(s) | https://www.ceremade.dauphine.fr/~cohen/mypapers/SpecialIssueIRBM2014.pdf |
| Alternate Webpage(s) | http://www.em-consulte.com/showarticlefile/873556/main.pdf |
| Alternate Webpage(s) | https://doi.org/10.1016/j.irbm.2014.02.001 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Issue |
