A Fast and Robust Graph-Based Approach for Boundary Estimation of Fiber Bundles Relying on Fractional Anisotropy Maps

Bauer, Mathias; Egger, Jan; O'Donnell, Tom; Barbieri, Sebastiano; Klein, Jan; Freisleben, Bernd; Hahn, H. K.; Nimsky, Christopher

doi:10.1109/icpr.2010.1155

Cited by 16 publications

(9 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…• the plausibility, as described in Section 4.2, is above a certain threshold • the plausibility, as described in Section 4.2 but without scaling by the average variance (thus just comparing main diffusion directions), is above a certain threshold • it is part of the morphological dilation of the set of voxels {V i } • it results from the min-cut-based approach presented in Bauer et al (2010).…”

Section: Resultsmentioning

confidence: 99%

Segmentation of fiber tracts based on an accuracy analysis on diffusion tensor software phantoms

et al. 2011

Self Cite

View full text Add to dashboard Cite

Section: Resultsmentioning

confidence: 99%

Segmentation of fiber tracts based on an accuracy analysis on diffusion tensor software phantoms

et al. 2011

Self Cite

View full text Add to dashboard Cite

“…However, instead of initializing the foreground and background on three single 2D slices, one single 3D initialization could be used by means of generating a sphere around the position of a user-defined seed point near the center of the vertebral body. Furthermore, we want to test GrowCut on longitudinal/tubular structures, like vessels [34][35][36][37] , fiber tracts 38,39 or the rectum [40][41][42] .…”

Section: Discussionmentioning

confidence: 99%

Cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures

Egger

Nimsky

2016

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

Due to the aging population, spinal diseases get more and more common nowadays; e.g., lifetime risk of osteoporotic fracture is 40% for white women and 13% for white men in the United States. Thus the numbers of surgical spinal procedures are also increasing with the aging population and precise diagnosis plays a vital role in reducing complication and recurrence of symptoms. Spinal imaging of vertebral column is a tedious process subjected to interpretation errors. In this contribution, we aim to reduce time and error for vertebral interpretation by applying and studying the GrowCutalgorithm for boundary segmentation between vertebral body compacta and surrounding structures. GrowCut is a competitive region growing algorithm using cellular automata. For our study, vertebral T2-weighted Magnetic Resonance Imaging (MRI) scans were first manually outlined by neurosurgeons. Then, the vertebral bodies were segmented in the medical images by a GrowCut-trained physician using the semi-automated GrowCut-algorithm. Afterwards, results of both segmentation processes were compared using the Dice Similarity Coefficient (DSC) and the Hausdorff Distance (HD) which yielded to a DSC of 82.99±5.03% and a HD of 18.91±7.2 voxel, respectively. In addition, the times have been measured during the manual and the GrowCut segmentations, showing that a GrowCutsegmentation -with an average time of less than six minutes (5.77±0.73) -is significantly shorter than a pure manual outlining.

show abstract

“…Another idea is to enhance the approach to 3D by outlining the structure in an axial, sagittal and coronal slice and creating a 3D graph for an interactive segmentation with this information. Finally, the approach can be used to segment other longitudinal/tubular structures, like fiber tracts [32][33][34] or the aorta to support the time-consuming analysis of aortic aneurysms [35][36][37][38][39] , which then can be used for virtual stenting [40][41][42][43] .…”

Section: Discussionmentioning

confidence: 99%

Interactive and scale invariant segmentation of the rectum/sigmoid via user-defined templates

Lüddemann¹,

Egger

2016

SPIE Proceedings

Self Cite

View full text Add to dashboard Cite

Among all types of cancer, gynecological malignancies belong to the 4 th most frequent type of cancer among women. Besides chemotherapy and external beam radiation, brachytherapy is the standard procedure for the treatment of these malignancies. In the progress of treatment planning, localization of the tumor as the target volume and adjacent organs of risks by segmentation is crucial to accomplish an optimal radiation distribution to the tumor while simultaneously preserving healthy tissue. Segmentation is performed manually and represents a time-consuming task in clinical daily routine. This study focuses on the segmentation of the rectum/sigmoid colon as an Organ-At-Risk in gynecological brachytherapy. The proposed segmentation method uses an interactive, graph-based segmentation scheme with a userdefined template. The scheme creates a directed two dimensional graph, followed by the minimal cost closed set computation on the graph, resulting in an outlining of the rectum. The graphs outline is dynamically adapted to the last calculated cut. Evaluation was performed by comparing manual segmentations of the rectum/sigmoid colon to results achieved with the proposed method. The comparison of the algorithmic to manual results yielded to a Dice Similarity Coefficient value of 83.85±4.08%, in comparison to 83.97±8.08% for the comparison of two manual segmentations of the same physician. Utilizing the proposed methodology resulted in a median time of 128 seconds per dataset, compared to 300 seconds needed for pure manual segmentation. DESCRIPTION OF PURPOSEGynecological malignancies which include endometrial, vaginal/vulvar and cervical cancers represent the 4 th most frequent type of cancer among women and a major cause of death around the world 1 . The standard procedure for primary or recurrent treatments of these types of cancer consists of external-beam radiation (EBR) followed by brachytherapy. During the brachytherapy procedure needle like catheters carrying a radiation source are inserted into the patient in close proximity to the tumor in order to directly irradiate the malignant tissue 2 . A crucial step in planning the applied amount and distribution of radiation is the segmentation of the tumor and adjacent organs-at-risk (OAR) potentially exposed to radiation. The most common OAR segmented in gynecological brachytherapy include the urinary bladder and the rectum/sigmoid colon. In general cases, the performing physician might have to outline several structures in more than 80 slices, which is a tedious task.Over the last decades various fully automatic segmentation methods have been proposed to support this timeconsuming segmentation process. However, the development of fully automatic segmentation tools remains problematic due to variability in pelvic organ shape and poor soft tissue depiction. None of these automatic analysis tools can guarantee robust results or achieved clinical approval. Moreover, they mostly lack necessary intervention methodologies and provide little final control by the medical do...

show abstract

A Fast and Robust Graph-Based Approach for Boundary Estimation of Fiber Bundles Relying on Fractional Anisotropy Maps

Cited by 16 publications

References 8 publications

Segmentation of fiber tracts based on an accuracy analysis on diffusion tensor software phantoms

Segmentation of fiber tracts based on an accuracy analysis on diffusion tensor software phantoms

Cellular automata segmentation of the boundary between the compacta of vertebral bodies and surrounding structures

Interactive and scale invariant segmentation of the rectum/sigmoid via user-defined templates

Contact Info

Product

Resources

About