Segmentation of polycystic kidneys from MR images

Dimitri Racimora; Pierre-Hugues Vivier; Hersh Chandarana; Henry Rusinek

doi:10.1117/12.844361

9 March 2010 Segmentation of polycystic kidneys from MR images

Dimitri Racimora, Pierre-Hugues Vivier, Hersh Chandarana, Henry Rusinek

Proceedings Volume 7624, Medical Imaging 2010: Computer-Aided Diagnosis; 76241W (2010) https://doi.org/10.1117/12.844361
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

Polycystic kidney disease (PKD) is a disorder characterized by the growth of numerous fluid filled cysts in the kidneys. Measuring cystic kidney volume is thus crucial to monitoring the evolution of the disease. While T2-weighted MRI delineates the organ, automatic segmentation is very difficult due to highly variable shape and image contrast. The interactive stereology methods used currently involve a compromise between segmentation accuracy and time. We have investigated semi-automated methods: active contours and a sub-voxel morphology based algorithm. Coronal T2- weighted images of 17 patients were acquired in four breath-holds using the HASTE sequence on a 1.5 Tesla MRI unit. The segmentation results were compared to ground truth kidney masks obtained as a consensus of experts. Automatic active contour algorithm yielded an average 22% ± 8.6% volume error. A recently developed method (Bridge Burner) based on thresholding and constrained morphology failed to separate PKD from the spleen, yielding 37.4% ± 8.7% volume error. Manual post-editing reduced the volume error to 3.2% ± 0.8% for active contours and 3.2% ± 0.6% for Bridge Burner. The total time (automated algorithm plus editing) was 15 min ± 5 min for active contours and 19 min ± 11 min for Bridge Burner. The average volume errors for stereology method were 5.9%, 6.2%, 5.4% for mesh size 6.6, 11, 16.5 mm. The average processing times were 17, 7, 4 min. These results show that nearly two-fold improvement in PKD segmentation accuracy over stereology technique can be achieved with a combination of active contours and postediting.

Citation Download Citation

Dimitri Racimora, Pierre-Hugues Vivier, Hersh Chandarana, and Henry Rusinek "Segmentation of polycystic kidneys from MR images", Proc. SPIE 7624, Medical Imaging 2010: Computer-Aided Diagnosis, 76241W (9 March 2010); https://doi.org/10.1117/12.844361

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