{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T22:11:57Z","timestamp":1769551917425,"version":"3.49.0"},"reference-count":19,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T00:00:00Z","timestamp":1769472000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Endoscopes are widely used in medicine, making objective evaluation of imaging performance essential for device development and quality assurance. Image resolution is commonly characterized by the modulation transfer function (MTF); however, its interpretation depends critically on how spatial frequency is defined and reported. Because spatial frequency is directly tied to sampling, it can be expressed in different units across the imaging chain, including the object plane, image sensor plane, and digital image domain. Inconsistent conversion between these spaces and domains can mislead comparisons and even alter the apparent ranking of regions of interest (ROIs) or imaging systems. This work presents a systematic analysis of spatial-frequency relationships along the endoscopic imaging chain and provides a practical conversion and interpretation workflow for MTF analysis. The framework accounts for sensor sampling, in-camera processing, resampling or scaling, and geometric distortion. Because geometric distortion introduces position-dependent sampling across the field of view, ROI-specific local-magnification measurements are incorporated to convert measured MTFs to a consistent object space spatial-frequency axis. Two case studies illustrate the implications. First, an off-axis ROI may appear to outperform the image center when MTF is expressed in digital image domain cycles per pixel, but this conclusion reverses after conversion to object space cycles per millimeter using local magnification. Second, resampled image outputs can yield inflated MTF curves unless scaling differences between formats are explicitly incorporated into the spatial-frequency axis. Overall, the proposed conversion and reporting workflow enables consistent and physically meaningful MTF comparison across devices, ROIs, and acquisition configurations when geometric distortion, sampling, or resampling differs, clarifying how optics, sensor characteristics, and image processing jointly determine reported MTF results.<\/jats:p>","DOI":"10.3390\/s26030827","type":"journal-article","created":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T09:05:27Z","timestamp":1769504727000},"page":"827","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Interpreting Modulation Transfer Function in Endoscopic Imaging: Spatial-Frequency Conversion Across Imaging Spaces and the Digital Image Domain with Case Studies"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0557-7058","authenticated-orcid":false,"given":"Quanzeng","family":"Wang","sequence":"first","affiliation":[{"name":"Center for Devices and Radiological Health, U.S. Food and Drug Administration, Silver Spring, MD 20993, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,27]]},"reference":[{"key":"ref_1","unstructured":"(2020). 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Sensors, 24.","DOI":"10.3390\/s24155075"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1863","DOI":"10.1364\/OSAC.2.001863","article-title":"Improved texture reproduction assessment of camera-phone-based medical devices with a dead leaves target","volume":"2","author":"Suresh","year":"2019","journal-title":"OSA Contin."},{"key":"ref_18","unstructured":"(2015). Photography\u2014Digital Cameras\u2014Geometric Distortion (GD) Measurements (Standard No. ISO 17850)."},{"key":"ref_19","unstructured":"(2017). 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