3D Scintillation Positioning Method in a Breast-specific Gamma Camera
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
In modern clinical practice, gamma camera is one of the most important imaging modalities for tumour diagnosis. The standard technique uses scintillator-based gamma cameras equipped with parallel-hole collimator to detect the planar position of γ photon interaction (scintillation). However, the positioning is of insufficient resolution and linearity for breast imaging. With the aim to improve spatial resolution and positioning linearity, a new gamma camera configuration was described specifically for breast-imaging. This breast-specific gamma camera was supposed to have the following technical features: variable angle slant-hole collimator; double SiPM arrays readout at the front and back sides of the scintillator; diffusive reflectors at the edges around the scintillator. Because slant-hole collimator was used, a new 3D scintillation positioning method was introduced and tested. The setup of the gamma detector was created in a Monte Carlo simulation toolkit, and a library of a number of light distributions from known positions was acquired through optical simulation. Two library-based positioning algorithms, similarity comparison and maximum likelihood, were developed to estimate the 3D scintillation position by comparing the responses from simulated gamma interactions and the responses from library. Results indicated that the planar spatial resolution and positioning linearity estimated with this gamma detector setup and positioning algorithm was higher than the conventional gamma detectors. The depth-of-interaction estimation was also of high linearity and resolution. With the results presented, the gamma detector setup and positioning method is promising in future breast cancer diagnosis.
Place, publisher, year, edition, pages
2015. , 96 p.
gamma camera, breast imaging, monte carlo simulation, depth of interaction
IdentifiersURN: urn:nbn:se:kth:diva-176453OAI: oai:DiVA.org:kth-176453DiVA: diva2:867213
Subject / course
Master of Science in Engineering - Medical Engineering
2015-06-11, 3-221, Alfred Nobels Allé 10, Huddinge, 10:00 (English)
Bennati, Paolo, Doctor
Nilsson, Mats, Doctor