[{"publication_status":"published","series_title":"Studies in Health Technology and Informatics","publisher":"IOS Press, Incorporated","abstract":[{"text":"Medical images need annotations with high-level semantic descriptors, so that domain experts can search for the desired dataset among an enormous volume of visual media within a Medical Data Integration Center. This article introduces a processing pipeline for storing and annotating DICOM and PNG imaging data by applying Elasticsearch, S3 and Deep Learning technologies. The proposed method processes both DICOM and PNG images to generate annotations. These image annotations are indexed in Elasticsearch with the corresponding raw data paths, where they can be retrieved and analyzed.","lang":"eng"}],"department":[{"_id":"DEP5023"}],"conference":{"start_date":"2023-08-08","end_date":"2023-08-12","location":"Sydney, AUSTRALIA","name":"19th World Congress on Medical and Health Informatics (MEDINFO)"},"intvolume":"       310","user_id":"83781","type":"conference_speech","doi":"10.3233/SHTI231208","_id":"12816","citation":{"short":"K.Y. Cheng, S. Pazmino, B. Bergh, M. Lange-Hegermann, B. Schreiweis, An Image Retrieval Pipeline in a Medical Data Integration Center., IOS Press, Incorporated, 2024.","chicago-de":"Cheng, Ka Yung, Santiago Pazmino, Bjoern Bergh, Markus Lange-Hegermann und Bjorn Schreiweis. 2024. <i>An Image Retrieval Pipeline in a Medical Data Integration Center.</i> <i>19th World Congress on Medical and Health Informatics (MEDINFO)</i>. Bd. 310. Studies in Health Technology and Informatics. IOS Press, Incorporated. doi:<a href=\"https://doi.org/10.3233/SHTI231208\">10.3233/SHTI231208</a>, .","din1505-2-1":"<span style=\"font-variant:small-caps;\">Cheng, Ka Yung</span> ; <span style=\"font-variant:small-caps;\">Pazmino, Santiago</span> ; <span style=\"font-variant:small-caps;\">Bergh, Bjoern</span> ; <span style=\"font-variant:small-caps;\">Lange-Hegermann, Markus</span> ; <span style=\"font-variant:small-caps;\">Schreiweis, Bjorn</span>: <i>An Image Retrieval Pipeline in a Medical Data Integration Center.</i>, <i>Studies in Health Technology and Informatics</i>. Bd. 310 : IOS Press, Incorporated, 2024","ieee":"K. Y. Cheng, S. Pazmino, B. Bergh, M. Lange-Hegermann, and B. Schreiweis, <i>An Image Retrieval Pipeline in a Medical Data Integration Center.</i>, vol. 310. IOS Press, Incorporated, 2024, pp. 1388–1389. doi: <a href=\"https://doi.org/10.3233/SHTI231208\">10.3233/SHTI231208</a>.","apa":"Cheng, K. Y., Pazmino, S., Bergh, B., Lange-Hegermann, M., &#38; Schreiweis, B. (2024). An Image Retrieval Pipeline in a Medical Data Integration Center. In <i>19th World Congress on Medical and Health Informatics (MEDINFO)</i> (Vol. 310, pp. 1388–1389). IOS Press, Incorporated. <a href=\"https://doi.org/10.3233/SHTI231208\">https://doi.org/10.3233/SHTI231208</a>","chicago":"Cheng, Ka Yung, Santiago Pazmino, Bjoern Bergh, Markus Lange-Hegermann, and Bjorn Schreiweis. <i>An Image Retrieval Pipeline in a Medical Data Integration Center.</i> <i>19th World Congress on Medical and Health Informatics (MEDINFO)</i>. Vol. 310. Studies in Health Technology and Informatics. IOS Press, Incorporated, 2024. <a href=\"https://doi.org/10.3233/SHTI231208\">https://doi.org/10.3233/SHTI231208</a>.","ama":"Cheng KY, Pazmino S, Bergh B, Lange-Hegermann M, Schreiweis B. <i>An Image Retrieval Pipeline in a Medical Data Integration Center.</i> Vol 310. IOS Press, Incorporated; 2024:1388-1389. doi:<a href=\"https://doi.org/10.3233/SHTI231208\">10.3233/SHTI231208</a>","van":"Cheng KY, Pazmino S, Bergh B, Lange-Hegermann M, Schreiweis B. An Image Retrieval Pipeline in a Medical Data Integration Center. 19th World Congress on Medical and Health Informatics (MEDINFO). IOS Press, Incorporated; 2024. (Studies in Health Technology and Informatics; vol. 310).","mla":"Cheng, Ka Yung, et al. “An Image Retrieval Pipeline in a Medical Data Integration Center.” <i>19th World Congress on Medical and Health Informatics (MEDINFO)</i>, vol. 310, IOS Press, Incorporated, 2024, pp. 1388–89, <a href=\"https://doi.org/10.3233/SHTI231208\">https://doi.org/10.3233/SHTI231208</a>.","bjps":"<b>Cheng KY <i>et al.</i></b> (2024) <i>An Image Retrieval Pipeline in a Medical Data Integration Center.</i> IOS Press, Incorporated.","havard":"K.Y. Cheng, S. Pazmino, B. Bergh, M. Lange-Hegermann, B. Schreiweis, An Image Retrieval Pipeline in a Medical Data Integration Center., IOS Press, Incorporated, 2024.","ufg":"<b>Cheng, Ka Yung u. a.</b>: An Image Retrieval Pipeline in a Medical Data Integration Center., Bd. 310, o. O. 2024 (Studies in Health Technology and Informatics)."},"volume":310,"title":"An Image Retrieval Pipeline in a Medical Data Integration Center.","page":"1388-1389","pmid":"1","status":"public","external_id":{"pmid":["38269660"]},"author":[{"full_name":"Cheng, Ka Yung","first_name":"Ka Yung","last_name":"Cheng"},{"first_name":"Santiago","last_name":"Pazmino","full_name":"Pazmino, Santiago"},{"full_name":"Bergh, Bjoern","last_name":"Bergh","first_name":"Bjoern"},{"last_name":"Lange-Hegermann","first_name":"Markus","id":"71761","full_name":"Lange-Hegermann, Markus"},{"last_name":"Schreiweis","full_name":"Schreiweis, Bjorn","first_name":"Bjorn"}],"year":"2024","date_updated":"2025-06-25T13:05:17Z","date_created":"2025-04-17T08:25:27Z","publication":"19th World Congress on Medical and Health Informatics (MEDINFO)","publication_identifier":{"eissn":["1879-8365"],"isbn":["978-1-64368-456-7"],"issn":["0926-9630"],"eisbn":["978-1-64368-457-4"]},"language":[{"iso":"eng"}],"keyword":["Medical image retrieval","data lake","DICOM","deep learning","elasticsearch"]},{"author":[{"last_name":"Cheng","first_name":"Ka Yung","full_name":"Cheng, Ka Yung"},{"first_name":"Markus","full_name":"Lange-Hegermann, Markus","id":"71761","last_name":"Lange-Hegermann"},{"last_name":"Hövener","first_name":"Jan-Bernd","full_name":"Hövener, Jan-Bernd"},{"full_name":"Schreiweis, Björn","first_name":"Björn","last_name":"Schreiweis"}],"year":"2024","external_id":{"pmid":["38975287"],"isi":["001257361300001"]},"pmid":"1","page":"434-450","status":"public","title":"Instance-level medical image classification for text-based retrieval in a medical data integration center","citation":{"apa":"Cheng, K. Y., Lange-Hegermann, M., Hövener, J.-B., &#38; Schreiweis, B. (2024). Instance-level medical image classification for text-based retrieval in a medical data integration center. <i>Computational and Structural Biotechnology Journal</i>, <i>24</i>, 434–450. <a href=\"https://doi.org/10.1016/j.csbj.2024.06.006\">https://doi.org/10.1016/j.csbj.2024.06.006</a>","chicago":"Cheng, Ka Yung, Markus Lange-Hegermann, Jan-Bernd Hövener, and Björn Schreiweis. “Instance-Level Medical Image Classification for Text-Based Retrieval in a Medical Data Integration Center.” <i>Computational and Structural Biotechnology Journal</i> 24 (2024): 434–50. <a href=\"https://doi.org/10.1016/j.csbj.2024.06.006\">https://doi.org/10.1016/j.csbj.2024.06.006</a>.","van":"Cheng KY, Lange-Hegermann M, Hövener JB, Schreiweis B. Instance-level medical image classification for text-based retrieval in a medical data integration center. Computational and Structural Biotechnology Journal. 2024;24:434–50.","ufg":"<b>Cheng, Ka Yung u. a.</b>: Instance-level medical image classification for text-based retrieval in a medical data integration center, in: <i>Computational and Structural Biotechnology Journal</i> 24 (2024),  S. 434–450.","mla":"Cheng, Ka Yung, et al. “Instance-Level Medical Image Classification for Text-Based Retrieval in a Medical Data Integration Center.” <i>Computational and Structural Biotechnology Journal</i>, vol. 24, 2024, pp. 434–50, <a href=\"https://doi.org/10.1016/j.csbj.2024.06.006\">https://doi.org/10.1016/j.csbj.2024.06.006</a>.","bjps":"<b>Cheng KY <i>et al.</i></b> (2024) Instance-Level Medical Image Classification for Text-Based Retrieval in a Medical Data Integration Center. <i>Computational and Structural Biotechnology Journal</i> <b>24</b>, 434–450.","havard":"K.Y. Cheng, M. Lange-Hegermann, J.-B. Hövener, B. Schreiweis, Instance-level medical image classification for text-based retrieval in a medical data integration center, Computational and Structural Biotechnology Journal. 24 (2024) 434–450.","short":"K.Y. Cheng, M. Lange-Hegermann, J.-B. Hövener, B. Schreiweis, Computational and Structural Biotechnology Journal 24 (2024) 434–450.","din1505-2-1":"<span style=\"font-variant:small-caps;\">Cheng, Ka Yung</span> ; <span style=\"font-variant:small-caps;\">Lange-Hegermann, Markus</span> ; <span style=\"font-variant:small-caps;\">Hövener, Jan-Bernd</span> ; <span style=\"font-variant:small-caps;\">Schreiweis, Björn</span>: Instance-level medical image classification for text-based retrieval in a medical data integration center. In: <i>Computational and Structural Biotechnology Journal</i> Bd. 24. Amsterdam [u.a.], Elsevier BV (2024), S. 434–450","chicago-de":"Cheng, Ka Yung, Markus Lange-Hegermann, Jan-Bernd Hövener und Björn Schreiweis. 2024. Instance-level medical image classification for text-based retrieval in a medical data integration center. <i>Computational and Structural Biotechnology Journal</i> 24: 434–450. doi:<a href=\"https://doi.org/10.1016/j.csbj.2024.06.006\">10.1016/j.csbj.2024.06.006</a>, .","ieee":"K. Y. Cheng, M. Lange-Hegermann, J.-B. Hövener, and B. Schreiweis, “Instance-level medical image classification for text-based retrieval in a medical data integration center,” <i>Computational and Structural Biotechnology Journal</i>, vol. 24, pp. 434–450, 2024, doi: <a href=\"https://doi.org/10.1016/j.csbj.2024.06.006\">10.1016/j.csbj.2024.06.006</a>.","ama":"Cheng KY, Lange-Hegermann M, Hövener JB, Schreiweis B. Instance-level medical image classification for text-based retrieval in a medical data integration center. <i>Computational and Structural Biotechnology Journal</i>. 2024;24:434-450. doi:<a href=\"https://doi.org/10.1016/j.csbj.2024.06.006\">10.1016/j.csbj.2024.06.006</a>"},"volume":24,"language":[{"iso":"eng"}],"keyword":["DICOM images","Medical image captioning","Medical image interchange","SNOMED CT body structure"],"date_created":"2025-04-22T13:32:38Z","publication":"Computational and Structural Biotechnology Journal","publication_identifier":{"issn":["2001-0370"]},"date_updated":"2025-06-26T08:58:59Z","department":[{"_id":"DEP5023"}],"abstract":[{"text":"A medical data integration center integrates a large volume of medical images from clinical departments, including X-rays, CT scans, and MRI scans. Ideally, all images should be indexed appropriately with standard clinical terms. However, some images have incorrect or missing annotations, which creates challenges in searching and integrating data centrally. To address this issue, accurate and meaningful descriptors are needed for indexing fields, enabling users to efficiently search for desired images and integrate them with international standards. This paper aims to provide concise annotation for missing or incorrectly indexed fields, incorporating essential instance -level information such as radiology modalities (e.g., X-rays), anatomical regions (e.g., chest), and body orientations (e.g., lateral) using a Deep Learning classification model - ResNet50. To demonstrate the capabilities of our algorithm in generating annotations for indexing fields, we conducted three experiments using two opensource datasets, the ROCO dataset, and the IRMA dataset, along with a custom dataset featuring SNOMED CT labels. While the outcomes of these experiments are satisfactory (Precision of >75%) for less critical tasks and serve as a valuable testing ground for image retrieval, they also underscore the need for further exploration of potential challenges. This essay elaborates on the identified issues and presents well-founded recommendations for refining and advancing our proposed approach.","lang":"eng"}],"publisher":"Elsevier BV","isi":"1","publication_status":"published","place":"Amsterdam [u.a.]","doi":"10.1016/j.csbj.2024.06.006","_id":"12822","type":"scientific_journal_article","user_id":"83781","intvolume":"        24"}]