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Listar por autor "Tabatabaei, Zahra"

Mostrando ítems 1-5 de 5

Advancing Content-Based Histopathological Image Retrieval Pre-Processing: A Comparative Analysis of the Effects of Color Normalization Techniques

Tabatabaei, Zahra; Pérez Bueno, Fernando; Colomer, Adrián; Oliver Moll, Javier; Molina, Rafael; Naranjo Ornedo, Valeriana (MDPI AG, 2024-03)

[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 ...
Deep Learning for Skin Melanocytic Tumors in Whole-Slide Images: A Systematic Review

Mosquera-Zamudio, Andrés; Launet, Laetitia; Tabatabaei, Zahra; Parra-Medina, Rafael; Colomer, Adrián; Oliver Moll, Javier; Monteagudo, Carlos; Janssen, Emiel; Naranjo Ornedo, Valeriana (MDPI AG, 2023-01)

[EN] Simple Summary Deep learning (DL) is expanding into the surgical pathology field and shows promising outcomes in diminishing subjective interpretations, especially in dermatopathology. We aim to show the efforts of ...
Deep learning strategies for histological image retrieval

Tabatabaei, Zahra (Universitat Politècnica de València, 2024-09-02)

[ES] Según World Health Organization (WHO), el cáncer es una de las principales causas de muerte a nivel mundial, con cerca de 10 millones de fallecimientos en 2020. Esto significa que aproximadamente una de cada seis ...
Toward More Transparent and Accurate Cancer Diagnosis With an Unsupervised CAE Approach

Tabatabaei, Zahra; Colomer, Adrián; Oliver Moll, Javier; Naranjo Ornedo, Valeriana (Institute of Electrical and Electronics Engineers, 2023-12-18)

[EN] According to the Global Cancer Observatory, 2020, breast cancer is the most prevalent cancer type in both genders (11.7%), while prostate cancer is the second most common cancer type in men (14.1%). In digital pathology, ...
WWFedCBMIR: World-Wide Federated Content-Based Medical Image Retrieval

Tabatabaei, Zahra; Wang, Yuandou; Colomer, Adrián; Oliver Moll, Javier; Zhao, Zhiming; Naranjo Ornedo, Valeriana (MDPI AG, 2023-09-28)

[EN] The paper proposes a federated content-based medical image retrieval (FedCBMIR) tool that utilizes federated learning (FL) to address the challenges of acquiring a diverse medical data set for training CBMIR models. ...