1 citations · 1 across the 6 of their papers we have counts for
6 papers
Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma
Francesca Fati, Felipe Coutinho, Marika Reinius +25
Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and spatial heterogeneity and is frequently diagnosed at an advanced stage. Neoadjuva…
Personalized Cell Segmentation: Benchmark and Framework for Reference-Guided Cell Type Segmentation
Bisheng Wang, Jaime S. Cardoso, Lin Wu
Accurate cell segmentation is critical for biological and medical imaging studies. Although recent deep learning models have advanced this task, most methods are limited to generic…
Leveraging Adversarial Learning for Pathological Fidelity in Virtual Staining
José Teixeira, Pascal Klöckner, Diana Montezuma +5
In addition to evaluating tumor morphology using H&E staining, immunohistochemistry is used to assess the presence of specific proteins within the tissue. However, this is a costly…
GANs vs. Diffusion Models for virtual staining with the HER2match dataset
Pascal Klöckner, José Teixeira, Diana Montezuma +3
Virtual staining is a promising technique that uses deep generative models to recreate histological stains, providing a faster and more cost-effective alternative to traditional ti…
CountPath: Automating Fragment Counting in Digital Pathology
Ana Beatriz Vieira, Maria Valente, Diana Montezuma +8
Quality control of medical images is a critical component of digital pathology, ensuring that diagnostic images meet required standards. A pre-analytical task within this process i…
A Survey on Cell Nuclei Instance Segmentation and Classification: Leveraging Context and Attention
João D. Nunes, Diana Montezuma, Domingos Oliveira +2
Manually annotating nuclei from the gigapixel Hematoxylin and Eosin (H&E)-stained Whole Slide Images (WSIs) is a laborious and costly task, meaning automated algorithms for cell nu…