Résumé
Single Photon Emission Computed Tomography(SPECT) imaging is pivotal for medical diagnosis, providingcrucial insights into a patient’s health. This medical imagingtechnique produces 3D images of a radioactive tracer’s distri-bution in the body, detected by a gamma camera. SPECT isused to visualize physiological processes in organs, diagnosingvarious diseases, thus providing essential functional information.However, interpreting SPECT images just like other medicalimaging results of organs near the lungs often encounterschallenges due to artifacts induced by respiratory motion, leadingto image noise and compromised quality.This study aims to enhance SPECT image clarity and fidelityfor organs near the lungs using center of gravity estimation andevent avoidance methods. By tracking respiratory movementswith a motion camera, image clarity is refined. Additionally,methods to enhance image quality without the motion cameraare explored. Calculating the barycenter allows for more accurateorgan positioning within specific timeframes, while eliminatingmotion in others streamlines events. The amalgamation of thesemethods results in a notable reduction in motion artifacts andimage blurring, with motion-corrected images exhibiting superiordelineation of structures compared to uncorrected ones. Thisprocess is helpful for the surgeon targeting the injection.