Mostrar el registro sencillo del ítem
dc.contributor.author | Tabatabaei, Zahra | es_ES |
dc.contributor.author | Pérez Bueno, Fernando | es_ES |
dc.contributor.author | Colomer, Adrián | es_ES |
dc.contributor.author | Oliver Moll, Javier | es_ES |
dc.contributor.author | Molina, Rafael | es_ES |
dc.contributor.author | Naranjo Ornedo, Valeriana | es_ES |
dc.date.accessioned | 2024-04-18T18:08:45Z | |
dc.date.available | 2024-04-18T18:08:45Z | |
dc.date.issued | 2024-03 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/203601 | |
dc.description.abstract | [EN] Content-Based Histopathological Image Retrieval (CBHIR) is a search technique based on the visual content and histopathological features of whole-slide images (WSIs). CBHIR tools assist pathologists to obtain a faster and more accurate cancer diagnosis. Stain variation between hospitals hampers the performance of CBHIR tools. This paper explores the effects of color normalization (CN) in a recently proposed CBHIR approach to tackle this issue. In this paper, three different CN techniques were used on the CAMELYON17 (CAM17) data set, which is a breast cancer data set. CAM17 consists of images taken using different staining protocols and scanners in five hospitals. Our experiments reveal that a proper CN technique, which can transfer the color version into the most similar median values, has a positive impact on the retrieval performance of the proposed CBHIR framework. According to the obtained results, using CN as a pre-processing step can improve the accuracy of the proposed CBHIR framework to 97% (a 14% increase), compared to working with the original images. | es_ES |
dc.description.sponsorship | Color normalization; Computer-aided diagnosis (CAD); Content-based image retrieval (CBIR); Histopathological images; Whole-slide images (WSIs) | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Applied Sciences | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject.classification | ESTADISTICA E INVESTIGACION OPERATIVA | es_ES |
dc.subject.classification | TEORÍA DE LA SEÑAL Y COMUNICACIONES | es_ES |
dc.title | Advancing Content-Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/app14052063 | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingeniería del Diseño - Escola Tècnica Superior d'Enginyeria del Disseny | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Telecomunicación - Escola Tècnica Superior d'Enginyers de Telecomunicació | es_ES |
dc.description.bibliographicCitation | Tabatabaei, Z.; Pérez Bueno, F.; Colomer, A.; Oliver Moll, J.; Molina, R.; Naranjo Ornedo, V. (2024). Advancing Content-Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques. Applied Sciences. 14(5). https://doi.org/10.3390/app14052063 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/app14052063 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 14 | es_ES |
dc.description.issue | 5 | es_ES |
dc.identifier.eissn | 2076-3417 | es_ES |
dc.relation.pasarela | S\511160 | es_ES |