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Nonetheless, outliers or artefacts still appear and need to be reliably detected to ensure a reliable diagnosis. Thus, the algorithms need to handle small sample sizes especially, when working with domain specific imaging modalities.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Methods<\/jats:title>\n                <jats:p>In this work, we suggest a pipeline for the detection and segmentation of light pollution in near-infrared fluorescence optical imaging (NIR-FOI), based on a small sample size. NIR-FOI produces spatio-temporal data with two spatial and one temporal dimension. To calculate a two-dimensional light pollution map for the entire image stack, we combine <jats:italic>region growing<\/jats:italic> and <jats:italic>k-nearest neighbours<\/jats:italic> (kNN), which classifies pixels into fore- and background by its entire temporal component. Thus, decision-making on reduced data is omitted.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>We achieved a <jats:inline-formula><jats:alternatives><jats:tex-math>$$F_1$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:msub>\n                      <mml:mi>F<\/mml:mi>\n                      <mml:mn>1<\/mml:mn>\n                    <\/mml:msub>\n                  <\/mml:math><\/jats:alternatives><\/jats:inline-formula> score of 0.99 for classifying a data set as light polluted or pollution-free. Additionally, we reached a total <jats:inline-formula><jats:alternatives><jats:tex-math>$$F_1$$<\/jats:tex-math><mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\">\n                    <mml:msub>\n                      <mml:mi>F<\/mml:mi>\n                      <mml:mn>1<\/mml:mn>\n                    <\/mml:msub>\n                  <\/mml:math><\/jats:alternatives><\/jats:inline-formula> score of 0.90 for detecting regions of interest within the polluted data sets. Finally, an average Dice\u2019s coefficient measuring the segmentation performance over all polluted data sets of 0.80 was accomplished.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusions<\/jats:title>\n                <jats:p>A Dice\u2019s coefficient of 0.80 for the area segmentation does not seem perfect. However, there are two main factors, besides true prediction errors, lowering the score: Segmentation mistakes on small areas lead to a rapid decrease in the score and labelling errors due to complex data. However, in combination with the light-polluted data set and pollution area detection, these results can be considered successful and play a key role in our general goal: Exploiting NIR-FOI for the early detection of arthritis within hand joints.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1007\/s11548-023-02951-w","type":"journal-article","created":{"date-parts":[[2023,6,4]],"date-time":"2023-06-04T09:01:45Z","timestamp":1685869305000},"page":"2063-2072","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Combining seeded region growing and k-nearest neighbours for the segmentation of routinely acquired spatio-temporal image data"],"prefix":"10.1007","volume":"18","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2006-3936","authenticated-orcid":false,"given":"Lukas","family":"Zerweck","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2073-6010","authenticated-orcid":false,"given":"Stefan","family":"Wesarg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1706-8979","authenticated-orcid":false,"given":"J\u00f6rn","family":"Kohlhammer","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3579-5574","authenticated-orcid":false,"given":"Michaela","family":"K\u00f6hm","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2023,6,4]]},"reference":[{"issue":"6","key":"2951_CR1","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1109\/34.295913","volume":"16","author":"R Adams","year":"1994","unstructured":"Adams R, Bischof L (1994) Seeded region growing. 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Approval was granted by the Ethics Committee of the of the University Hospital Frankfurt a. Main, Germany (Date: 16th Mai 2013, No.: 127\/13; Date: 16th Mai 2013, No.: 128\/13; Date: 10th April 2019, No.: 433\/18; Date: 28th Nov. 2018, No.: 454\/17).","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}},{"value":"All participants provided signed informed consent for inclusion in the studies and agreed to the usage of their data for research purposes. All participants were fully capable of giving informed consent for participation in a study.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"All participants agreed to publishing their data in an aggregated anonymized way.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}