11 papers
NucEval: A Robust Evaluation Framework for Nuclear Instance Segmentation
Amirreza Mahbod, Ramona Woitek, Jeanne Shen
In computational pathology, nuclear instance segmentation is a fundamental task with many downstream clinical applications. With the advent of deep learning, many approaches, inclu…
Effect of Patch Size on Fine-Tuning Vision Transformers in Two-Dimensional and Three-Dimensional Medical Image Classification
Massoud Dehghan, Ramona Woitek, Amirreza Mahbod
Vision Transformers (ViTs) and their variants have become state-of-the-art in many computer vision tasks and are widely used as backbones in large-scale vision and vision-language…
NucFuseRank: Dataset Fusion and Performance Ranking for Nuclei Instance Segmentation
Nima Torbati, Anastasia Meshcheryakova, Ramona Woitek +3
Nuclei instance segmentation in hematoxylin and eosin (H&E)-stained images plays an important role in automated histological image analysis, with various applications in downstream…
Developing Predictive and Robust Radiomics Models for Chemotherapy Response in High-Grade Serous Ovarian Carcinoma
Sepideh Hatamikia, Geevarghese George, Florian Schwarzhans +10
Objectives: High-grade serous ovarian carcinoma (HGSOC) is typically diagnosed at an advanced stage with extensive peritoneal metastases, making treatment challenging. Neoadjuvant…
Improved tissue sodium concentration quantification in breast cancer by reducing partial volume effects: a preliminary study
Olgica Zaric, Carmen Leser, Vladimir Juras +10
Introduction: In sodium (23Na) magnetic resonance imaging (MRI), partial volume effects (PVE) are one of the most common causes of errors in the in vivo quantification of tissue so…
ACS-SegNet: An Attention-Based CNN-SegFormer Segmentation Network for Tissue Segmentation in Histopathology
Nima Torbati, Anastasia Meshcheryakova, Ramona Woitek +2
Automated histopathological image analysis plays a vital role in computer-aided diagnosis of various diseases. Among developed algorithms, deep learning-based approaches have demon…