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Volumetric qualitative comparison of the accuracy of the segmented gray matter for the pairwise slice-based framework, and the proposed groupwise slice-based framework. The proposed registration framework consistently estimates the complex shape of the GM horn more accurately than its pairwise counterpart. Note the different axes for the two different registration frameworks.

Groupwise Multi-Atlas Segmentation of the Spinal Cord’s Internal Structure.

Apr. 15, 2014—Andrew J. Asman, Frederick W. Bryan, Seth A. Smith, Daniel S. Reich, Bennett A. Landman. “Groupwise Multi-Atlas Segmentation of the Spinal Cord’s Internal Structure.” Medical Image Analysis (MedIA). 2014 Feb 5;18(3):460-471. PMC24556080† Full Text:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4009677/ Abstract The spinal cord is an essential and vulnerable component of the central nervous system. Differentiating and localizing the spinal...

Qualitative fusion results. A representative slice shows the effect of the additional confidence parameter on the output of both the voting and statistical fusion techniques. The three rater observations (one submitted empty) are shown. In this example, CWV and “Best Pick” would result in an identical segmentation.

Self-Assessed Performance Improves Statistical Fusion of Image Labels.

Feb. 15, 2014—Frederick W. Bryan, Zhoubing Xu, Andrew J. Asman, Wade M. Allen, Daniel S. Reich, and Bennett A. Landman. “Self-Assessed Performance Improves Statistical Fusion of Image Labels.” Medical Physics. 2014 Mar;41(3):031903. PMC24593721† Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978333/ Abstract Purpose: Expert manual labeling is the gold standard for image segmentation, but this process is difficult, time-consuming, and prone...

Texture Analysis Improves Level Set Segmentation of the Anterior Abdominal Wall.

Dec. 15, 2013—Zhoubing Xu, Wade M. Allen, Rebeccah B. Baucom, Benjamin K. Poulose, Bennett A. Landman. “Texture Analysis Improves Level Set Segmentation of the Anterior Abdominal Wall.” Medical Physics. 2013 Dec;40(12):121901. † PMC3838426 Full Text: https://www.ncbi.nlm.nih.gov/pubmed/24320512 Abstract PURPOSE: The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is...

Qualitative results for the detection of malignant gliomas. Five representative examples are presented. For each example, the target volume, expert labeling, label fusion estimate, and the out-of-atlas likelihood are presented. The first four examples represent cases where the tumor region is correctly identified. The last example represents the outlier case [seen in Fig. Fig.2c]2c] in which the cancerous region was almost completely missed.

Out-of-Atlas Likelihood Estimation using Multi-Atlas Segmentation.

Apr. 15, 2013—Andrew J. Asman, Lola Chambless, Reid Thompson, and Bennett A. Landman. “Out-of-Atlas Likelihood Estimation using Multi-Atlas Segmentation.” Medical Physics. 2013 Apr;40(4) PMC23556928 † Full-Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3625241/ Abstract Purpose: Multi-atlas segmentation has been shown to be highly robust and accurate across an extraordinary range of potential applications. However, it is limited to the segmentation of structures...

Each of the 567 DTI datasets was characterized by a 112 element vector of stored outputs from the pipeline. PCA analysis was performed on the resulting data. (A) DTI dataset locations in the first two dimensions of the PCA analysis. Data is symbolized by study Roman numeral (Table 1). Single arrow points to a data quality outlier from study I; subject 3 in Figure 4 and in (B). A double headed arrow points to a cluster representing an isolated protocol sub-group from study VI. (B) FA maps from similar sagittal slice locations in two subjects from Study I. Subject 4 is the indicated outlier in (A) and subject 5 was selected from the center of the study I cluster seen in (A).

Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging.

Apr. 15, 2013—Carolyn B. Lauzon, Andrew J. Asman, Michael L. Esparza, Scott S. Burns, Qiuyun Fan, Yurui Gao, Adam W. Anderson, Nicole Davis, Laurie E. Cutting, Bennett A. Landman. “Simultaneous Analysis and Quality Assurance for Diffusion Tensor Imaging.” PLoS ONE. 2013 Apr 30;8(4) PMC23637895 † Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3640065/ Abstract Diffusion tensor imaging (DTI) enables non-invasive, cyto-architectural...

Illustrations of the proposed system in use. (a) Surgeon using the system. (b) Virtual hand interacting with 3D abdominal model. (c) Navigation of axial slices. (d) Navigation of sagittal slices.

Immersive Virtual Reality for Visualization of Abdominal CT.

Feb. 15, 2013—Qiufeng Lin, Zhoubing Xu, Rebeccah Baucom, Benjamin Poulose, Bennett A. Landman, Robert E. Bodenheimer. “Immersive Virtual Reality for Visualization of Abdominal CT.” In Proceedings of the SPIE Medical Imaging Conference. Orlando, Florida, February 2013† Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877248/ Abstract Immersive virtual environments use a stereoscopic head-mounted display and data glove to create high fidelity virtual experiences...

Example qualitative results. Three representative slices from three different brains are presented for comparison. For each example, the target, truth labels, an example atlas, the label fusion estimate and the cancer likelihood estimate are presented. Note the high quality likelihood estimate in the first two examples. On the third example, the cancer is detected, but it is not as well localized as in the first two examples.

Out-of-Atlas Labeling: A Multi-Atlas Approach to Cancer Segmentation

Dec. 31, 2012—Andrew J. Asman and Bennett A. Landman, “Out-of-Atlas Labeling: A Multi-Atlas Approach to Cancer Segmentation”, In Proceedings of the 2012 International Symposium on Biomedical Imaging (ISBI). Barcelona, Spain† Full Text: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3892947/ Abstract Conventional automated segmentation techniques for magnetic resonance imaging (MRI) fail to perform in a robust and consistent manner when brain anatomy differs...