Awards

Unknown

Fractal Features for Diagnosing Mammographic Masses

Phase 1 SBIR

Agency: Department of Health & Human Services
Topic:
Budget: 04/01/98 - 03/31/99
PI: Alan I. Penn

We propose developing statistical fractal features which quantify lesion border roughness on mammograms and using these features to distinguish malignant and benign breast lesions. Objective measures of lesion roughness are important in the diagnosis and staging of breast cancer. In this novel approach,...

Unknown

Fractal Dimension Features for MRI Breast Mass Analysis

Phase 1 SBIR

Agency: Department of Health & Human Services
Topic:
Budget: 09/09/97 - 03/24/99
PI: Alan I. Penn

We propose developing a robust algorithm to evaluate the fractal dimension (fd) of borders of Magnetic Resonance (MR) images of breast masses which contain a small number of pixels. The fd algorithm will be evaluated in upcoming MR breast clinical trials and will be marketed to developers of computer-...

Unknown

Fractal Algorithms for Compressing Chest-imaging Data

Phase 1 SBIR

Agency: Department of Health & Human Services
Topic:
Budget: 09/30/93 - 09/30/94
PI: Alan I. Penn

The proposed research will result in a computerized system that uses fractal algorithms for compressing and decompressing digitized images of chest x-rays and analyzing recurrent geometric patterns. Utilizing a combination of general purpose fractal compression with customized fractal algorithms for recurrent geometrical patterns, this approach...