{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T07:13:28Z","timestamp":1777446808074,"version":"3.51.4"},"reference-count":34,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2018,5,6]],"date-time":"2018-05-06T00:00:00Z","timestamp":1525564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Imaging"],"abstract":"<jats:p>One of the most challenging computer vision problems in the plant sciences is the segmentation of roots and soil in X-ray tomography. So far, this has been addressed using classical image analysis methods. In this paper, we address this soil\u2013root segmentation problem in X-ray tomography using a variant of supervised deep learning-based classification called transfer learning where the learning stage is based on simulated data. The robustness of this technique, tested for the first time with this plant science problem, is established using soil\u2013roots with very low contrast in X-ray tomography. We also demonstrate the possibility of efficiently segmenting the root from the soil while learning using purely synthetic soil and roots.<\/jats:p>","DOI":"10.3390\/jimaging4050065","type":"journal-article","created":{"date-parts":[[2018,5,7]],"date-time":"2018-05-07T03:12:21Z","timestamp":1525662741000},"page":"65","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Transfer Learning from Synthetic Data Applied to Soil\u2013Root Segmentation in X-Ray Tomography Images"],"prefix":"10.3390","volume":"4","author":[{"given":"Cl\u00e9ment","family":"Douarre","sequence":"first","affiliation":[{"name":"Laris, UMR INRA IRHS, Universit\u00e9 d\u2019Angers, 62 avenue Notre Dame du Lac, 49000 Angers, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard","family":"Schielein","sequence":"additional","affiliation":[{"name":"Development Center X-Ray Technology EZRT, Fraunhofer Institute for Integrated Systems IIS, Flugplatzstra\u00dfe 75, 90768 F\u00fcrth, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Carole","family":"Frindel","sequence":"additional","affiliation":[{"name":"CREATIS, Universit\u00e9 Lyon1, CNRS UMR5220, INSERM U1206, INSA-Lyon, 69621 Villeurbanne, France"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stefan","family":"Gerth","sequence":"additional","affiliation":[{"name":"Development Center X-Ray Technology EZRT, Fraunhofer Institute for Integrated Systems IIS, Flugplatzstra\u00dfe 75, 90768 F\u00fcrth, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"David","family":"Rousseau","sequence":"additional","affiliation":[{"name":"Laris, UMR INRA IRHS, Universit\u00e9 d\u2019Angers, 62 avenue Notre Dame du Lac, 49000 Angers, France"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,5,6]]},"reference":[{"key":"ref_1","unstructured":"Goodfellow, I., Bengio, Y., Courville, A., and Bengio, Y. 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