SBIR-STTR Award

Morphometric analysis is a primary algorithmic tool to discover disease and drug related effects on brain anatomy. Neurological degeneration and disease manifest in subtle and varied changes in brain anatomy that can be non-local in nature and effect amounts of white and gray matter as well as relative positioning and shapes of local brain anatomy. State-of-the-art morphometry methods focus on local matter distribution or on shape variations of apriori selected anatomies but have difficulty in detecting global or regional deterioration of matter; an important effect in many neurodegenerative processes. The proposal team recently developed a morphometric analysis based on unbalanced optimal transport, called UTM, that promises to be capable to discover local and global alteration of matter without the need to apriori select an anatomical region of interest. The goal of this proposal is to develop the UTM technology into a software tool for automated high-throughput screening of large neurological image data sets. ?A more sensitive automated morphometric analysis tool will help researchers to discover neurological effects related to disease and lead to more efficient screening for drug related effects.

Public Health Relevance Statement:
Project Narrative Describing anatomical differences in neurological image data set is a key technology to non-invasively discover the effects of disease processes or drug treatments on brain anatomy. Current morphometric analysis focus on local matter composition and on the shape of a priori defined regions of interest. The goal of this proposal is to extend the capabilities of image based morphometric analysis to be able to discover regionally varying deterioration and alteration of matter without the need for fine-grained segmentations and a priori definitions of regions of interest.

Project Terms:
Algorithmic Software; Algorithms; Alzheimer's Disease; Anatomy; Autistic Disorder; base; Brain; Calibration; Clinical; clinical Diagnosis; Clinical Research; Cluster Analysis; Computer software; Data Set; Databases; Dementia; Deterioration; Development; Diffuse; Disease; Drug Screening; Early Diagnosis; experience; Foundations; frontal lobe; Goals; Grain; gray matter; high throughput screening; Image; Image Analysis; image processing; image registration; Imagery; imaging capabilities; improved; interest; Internet; Lead; learning strategy; Location; Machine Learning; Medical Imaging; Methodology; Methods; Modality; morphometry; Nature; Nerve Degeneration; nervous system disorder; Neurologic; Neurologic Effect; Online Systems; Outcome; Pharmaceutical Preparations; Pharmacotherapy; Phase; Population Study; Positioning Attribute; Positron-Emission Tomography; predict clinical outcome; predictive modeling; Process; programs; Research; research and development; Research Personnel; Services; shape analysis; Shapes; software development; Software Tools; task analysis; Technology; Temporal Lobe; Testing; tool; Validation; Variant; web services; white matter

Morphometric analysis is a primary algorithmic tool to discover disease and drug related effects on brain anatomy. Neurological degeneration and disease manifest in subtle and varied changes in brain anatomy that can be non-local in nature and effect amounts of white and gray matter as well as relative positioning and shapes of local brain anatomy. State-of-the-art morphometry methods focus on local matter distribution or on shape variations of apriori selected anatomies but have difficulty in detecting global or regional deterioration of matter; an important effect in many neurodegenerative processes. The proposal team recently developed a morphometric analysis based on unbalanced optimal transport, called UTM, that promises to be capable to discover local and global alteration of matter without the need to apriori select an anatomical region of interest. The goal of this proposal is to develop the UTM technology into a software tool for automated high-throughput screening of large neurological image data sets. ?A more sensitive automated morphometric analysis tool will help researchers to discover neurological effects related to disease and lead to more efficient screening for drug related effects.

Public Health Relevance Statement:
Project Narrative Describing anatomical differences in neurological image data set is a key technology to non-invasively discover the effects of disease processes or drug treatments on brain anatomy. Current morphometric analysis focus on local matter composition and on the shape of a priori defined regions of interest. The goal of this proposal is to extend the capabilities of image based morphometric analysis to be able to discover regionally varying deterioration and alteration of matter without the need for fine-grained segmentations and a priori definitions of regions of interest.

NIH Spending Category:
Acquired Cognitive Impairment; Bioengineering; Brain Disorders; Clinical Research; Data Science; Dementia; HIV/AIDS; Machine Learning and Artificial Intelligence; Mental Health; Networking and Information Technology R&D (NITRD); Neurodegenerative; Neurosciences

Project Terms:
Algorithmic Software; Algorithms; Alzheimer's Disease; Anatomy; autism spectrum disorder; base; Brain; Calibration; Clinical; clinical Diagnosis; Clinical Research; Cluster Analysis; Computer software; Data Set; Databases; Dementia; Deterioration; Development; Diffuse; Disease; Drug Screening; Early Diagnosis; experience; Foundations; frontal lobe; Goals; Grain; gray matter; high throughput screening; Image; Image Analysis; image processing; image registration; Imagery; imaging capabilities; improved; interest; Internet; Lead; learning strategy; Location; Machine Learning; Medical Imaging; Methodology; Methods; Modality; morphometry; Nature; Nerve Degeneration; nervous system disorder; Neurologic; Neurologic Effect; Online Systems; Outcome; Pharmaceutical Preparations; Pharmacotherapy; Phase; Population Study; Positioning Attribute; Positron-Emission Tomography; predict clinical outcome; predictive modeling; Process; programs; Research; research and development; Research Personnel; Services; shape analysis; Shapes; software development; Software Tools; Structure; task analysis; Technology; Temporal Lobe; Testing; tool; Validation; Variant; web services; white matter