Maximum entropy and the concept of feasibility in tomographic image reconstruction

Conference · Sun Jan 01 04:00:00 EST 1989

DOI:https://doi.org/10.1117/12.953221· OSTI ID:5997301

Nunez, J.; Llacer, J.

Feasible images in tomographic image reconstruction are defined as those images compatible with the data by consideration of the statistical process that governs the physics of the problem. The first part of this paper reviews the concept of image feasibility, discusses its theoretical problems and practical advantages, and presents an assumption justifying the method and some preliminary results supporting it. In the second part of the paper two different algorithms for tomographic image reconstruction are developed. The first is a Maximum Entropy algorithm and the second is a full Bayesian algorithm. Both algorithms are tested for feasibility of the resulting images, and we show that the Bayesian method yields feasible reconstructions in Positron Emission Tomography. 25 refs., 3 figs.

• Research Organization: Lawrence Berkeley Lab., CA (USA)
• DOE Contract Number: AC03-76SF00098
• OSTI ID: 5997301
• Report Number(s): LBL-25451; CONF-890115-2; ON: DE89014886
• Country of Publication: United States
• Language: English

Related Subjects

550602* -- Medicine-- External Radiation in Diagnostics-- (1980-)
62 RADIOLOGY AND NUCLEAR MEDICINE
COMPUTERIZED TOMOGRAPHY
DIAGNOSTIC TECHNIQUES
EMISSION COMPUTED TOMOGRAPHY
ENTROPY
EVALUATION
IMAGE PROCESSING
OPTIMIZATION
PHYSICAL PROPERTIES
PROCESSING
RESPONSE MODIFYING FACTORS
THERMODYNAMIC PROPERTIES
TOMOGRAPHY