USA flag logo/image

An Official Website of the United States Government

IGF::OT::IGF OTHER FUNCTIONS SCALABLE AUTOMATED BRAIN TUMOR SEGMENTATION

Award Information

Agency:
Department of Health and Human Services
Branch:
N/A
Award ID:
Program Year/Program:
2012 / SBIR
Agency Tracking Number:
N43CO120032
Solicitation Year:
2012
Solicitation Topic Code:
NCI
Solicitation Number:
Small Business Information
Infotech Soft, Inc.
1201 Brickell Ave, Suite 220 Miami, FL 33131-
View profile »
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2012
Title: IGF::OT::IGF OTHER FUNCTIONS SCALABLE AUTOMATED BRAIN TUMOR SEGMENTATION
Agency: HHS
Contract: N43CO120032
Award Amount: $199,969.00
 

Abstract:

Brain tumor segmentation in Magnetic Resonance Imaging is an important task for neurosurgeons, oncologists, and radiologists to assess disease burden and measure tumor response to treatment. In 2008, over 237,000 individuals worldwide are estimated to havebeen diagnosed with malignant brain and central nervous system tumors with over 174,000 deaths. Detection of brain tumors with the exact location and orientation is extremely important for effective diagnosis, treatment planning, and analysis of treatmenteffectiveness; however, manual delineation of the tumor takes considerable time and is prone to error and wide variability. The overall goal of this proposal is to develop a scalable and automated approach for the segmentation of brain tumors based on Hidden Markov Models (HMMs). The objectives of the project are: 1) Develop a tumor segmentation approach based on a novel utilization of HMMs for automated segmentation of multi-sequence brain MRI data for accurate and robust determination of tumor volume; 2)Design a MapReduce model for the HMM-based brain tumor segmentation approach to enable scalable development of the segmentation processes in a cluster environment; 3) Evaluate the HMM-based brain tumor segmentation framework in terms of accuracy, robustness, and performance in the context of multi-sequence MRI data.

Principal Investigator:

Patricia Buendia
305-371-5111
PATRICIA.BUENDIA@INFOTECHSOFT.COM

Business Contact:

Patricia Buendia
305-371-5111
PATRICIA.BUENDIA@INFOTECHSOFT.COM
Small Business Information at Submission:

INFOTECH SOFT, INC.
INFOTECH SOFT, INC. 1201 Brickell Ave MIAMI, FL 33131-

EIN/Tax ID: 650866069
DUNS: N/A
Number of Employees: N/A
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No