{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T14:19:03Z","timestamp":1788272343471,"version":"build-2803163510"},"reference-count":21,"publisher":"Wiley","issue":"8","license":[{"start":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:00:00Z","timestamp":1785283200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T00:00:00Z","timestamp":1785283200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aapm.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2026,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Projection and backprojection are fundamental operators in tomographic image reconstruction. Existing approaches\u2014namely pixel\u2010driven (PD), ray\u2010driven (RD), and distance\u2010driven (DD)\u2014are subject to well\u2010known trade\u2010offs among interpolation artifacts, geometric flexibility, and computational\u00a0cost.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Purpose<\/jats:title>\n                    <jats:p>This study aims to introduce a unified framework that systematically models and resolves the intrinsic limitations of current projection topologies. Within this framework, a novel topology called vector\u2010driven (VD) is proposed to improve geometric flexibility without sacrificing computational\u00a0efficiency.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A three\u2010level hierarchical formulation\u2014comprising topology, algorithm, and implementation\u2014is also developed to isolate the structural origins of artifacts and performance bottlenecks in projection operators. The proposed VD projection and backprojection method represents all tomographic system components as vectors in 3D space and performs non\u2010orthogonal projections that preserve geometric symmetry between forward and backward operations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Experimental validation was conducted using multiple geometric configurations, and quantitative image quality metrics (SSIM, RMSE, PSNR, NCC, UIQI) were compared against PD, RD, and DD baselines. VD produced artifact\u2010free output across all tested geometries and reached near\u2010perfect image\u2010quality scores matching the leading RD\u2010PD baseline combination. VD attained the shortest wall\u2010clock time in both directions, running about 37% faster than an optimised PD algorithm in forward projection and reaching near parity in backprojection, while remaining 31%\u201357% faster than De\u00a0Man's DD and 62%\u201382% faster than Siddon's RD in both directions. This advantage reflects VD's balanced profile of low arithmetic workload of 13.7\u201324.0\u00a0GFLOP per call (giga floating\u2010point operations), high pipeline efficiency with 3.6\u20134.4 instructions per cycle (IPC), and low DRAM traffic of about 5\u00a0GB read per\u00a0call.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>VD unifies forward and backward projection within a single vector\u2010based model and, in the configurations tested, performs competitively with established projection topologies in both accuracy and computational\u00a0cost.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/mp.70581","type":"journal-article","created":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T16:03:25Z","timestamp":1785341005000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Vector\u2010Driven Projection and Backprojection"],"prefix":"10.1002","volume":"53","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-4800-3098","authenticated-orcid":false,"given":"Ismail Melik","family":"Turker","sequence":"first","affiliation":[{"name":"Department of Electronics and Communication Engineering Istanbul Technical University Istanbul T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Isa","family":"Yildirim","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication Engineering Istanbul Technical University Istanbul T\u00fcrkiye"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2026,7,29]]},"reference":[{"key":"e_1_2_10_2_1","doi-asserted-by":"publisher","DOI":"10.1006\/rtim.1995.1002"},{"key":"e_1_2_10_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/23.322963"},{"key":"e_1_2_10_4_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNS.1981.4331812"},{"key":"e_1_2_10_5_1","doi-asserted-by":"publisher","DOI":"10.3233\/XST-17284"},{"key":"e_1_2_10_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.1982.4307572"},{"key":"e_1_2_10_7_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.595715"},{"issue":"4","key":"e_1_2_10_8_1","first-page":"909","article-title":"Efficient forward projection through discrete data sets using tri\u2010linear interpolation","volume":"18","author":"Kohler J","year":"1991","journal-title":"Med Phys"},{"key":"e_1_2_10_9_1","doi-asserted-by":"publisher","DOI":"10.1080\/00207160.2021.1969017"},{"key":"e_1_2_10_10_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4761867"},{"key":"e_1_2_10_11_1","doi-asserted-by":"crossref","unstructured":"ManBD BasuS.Distance\u2010driven projection and backprojection. 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