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Medical imaging research unifies CT, MRI, PET, SPECT reconstruction techniques

This paper presents a unified computational perspective on medical image acquisition and reconstruction, covering modalities like CT, MRI, PET, and SPECT. It details how these systems measure physical signals and use image reconstruction to solve inverse problems, highlighting the computational challenges posed by large datasets and advanced reconstruction methods. The work emphasizes the critical role of efficient computing, including optimization algorithms and parallel processing, in achieving clinically practical reconstruction times and improving image quality while reducing scan time or radiation dose. AI

IMPACT This research could lead to faster and more accurate medical image reconstruction, potentially improving diagnostic capabilities and patient care.

RANK_REASON The cluster contains a single academic paper on arXiv. [lever_c_demoted from research: ic=1 ai=0.7]

Read on arXiv cs.CV →

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Medical imaging research unifies CT, MRI, PET, SPECT reconstruction techniques

COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Xiao Wang, Jayasai Rajagopal, Md Safaiat Hossain, Peng Chen, Mohamed Wahib, Enzhi Zhang, Emma J. Reid ·

    Efficient Computing for Medical Image Acquisition and Reconstruction

    arXiv:2607.13204v1 Announce Type: cross Abstract: Medical imaging systems such as CT, MRI, PET, and SPECT do not directly acquire images. Instead, they measure physical signals that encode anatomical or physiological information, and image reconstruction recovers the underlying i…