3. CBL Roadmap New Computational Tools For Scientific Discovery From Algorithm to Bedside / TestBed Research Teams of the Future [email_address]

6. CS@UH research highlights: people’s hearts and minds [email_address] People’s hearts and minds

8. A Holistic Approach: Multiple scales Organ System Integrative and personalized biomedicine (prevention, diagnosis, treatment) is multidimensional so that systems approach has to build models based on data from all scale levels Cell Gene

12. Left Ventricular Segmentation in MR Images Objective: To develop an automated method for computing quantitative indices of ventricular morphology and function from volumetric MR images. Papillary muscles Partial voluming Fuzzy images Low contrast Challenges Methods LV localization using multiple views, intensity and morphological information Myocardial sample region estimation Hierarchical multi-class multi-feature fuzzy connectedness Optimal path computation using dynamic programming Polar transformation Results Goal: To develop a theoretical framework and computational tools to aid physicians in scoring a patient’s vulnerability and the likelihood of a future coronary event. Segmented end-diastolic myocardium The ejection fraction computed automatically for 20 subjects has +/-2% of mean bias when compared with manual readings by two experts. Segmented myocardium (end-diastole to end-systole) Segmented end-diastolic myocardium Impact: Cardiovascular disease (CVD) is the #1 killer in the United States. This work will aid physicians in early diagnosis and treatment planning of CVD.

16. Intravascular Ultrasound-based Detection of Vasa Vasorum Challenges Results Methods Inter-frame motion Image stabilization & Elastic wall deformation Vasa vasorum (histology) After Injection Goal: Early detection of atherosclerotic plaques with a high probability of causing future complications (heart attack or stroke) Objective: Imaging and quantification of vasa vasorum (microvessels associated with plaque inflammation and vulnerability) through microbubble perfusion analysis Video Multidimensional scaling-based frame gating Rigid/elastic contour tracking Statistical frame comparison to capture changes due to vasa vasorum perfusion Before Microbubble Injection + Similarity matrix -> Frame similarity space -> Stabilized frame ensembles

18. Online Reconstruction and Functional Imaging of Neurons (ORION) Challenges Results Methods Objective: To produce libraries of neurons that can be used in on-line applications. Impact: To understand computational principles and cellular mechanisms that underlie brain function, in both normal and diseased states. Goal: Realtime mapping of functional imaging data (e.g., spatio-temporal patterns of dendritic voltages or intracellular ions) from neuronal structure during the critically limited duration of an acute experiment Original Volume Morphological Representation Intensity Decay Irregular Shape Noise and Image artifacts Frame Based Denoising Action potential simulation from reconstruction Spatial error: Max: 6.325 voxels Mean: 0.4 voxels Skeletonization and morphological description Segmentation Volume Registration and Frame-Based Denoising 100 µ m

19. Statistical Atlas-based Segmentation of Mouse Brain Tissue Slices Containing Gene Expression Data Objective: Automatically and accurately annotate anatomical regions in mouse brain tissue sections revealing gene expression patterns Methods Anatomical landmarks… … and region boundary information. Results Challenges Distorted topography Before fitting After fitting … hybrid atlas at multiple resolutions, including shape… Goal: Mapping of gene expression patterns at different developmental stages in the context of mouse brain anatomy Comparison with manual annotation Impact: Studying gene expression patterns in the mouse brain will greatly enhance our understanding of the function and diseases of the human brain Appearance variation Shape variation Missing parts Distorted topography Probability estimate for landmarks Atlas fitted to image

23. Data Availability Today Near Future

24. Analysis What we need now What we will need in the future Current technology

25. Roadmap New Computational Tools For Scientific Discovery From Algorithm to Bedside / TestBed Research Teams of the Future [email_address]