1 citations · 2 across the 4 of their papers we have counts for
6 papers
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…
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…
Fusion of Foundation and Vision Transformer Model Features for Dermatoscopic Image Classification
Amirreza Mahbod, Rupert Ecker, Ramona Woitek
Accurate classification of skin lesions from dermatoscopic images is essential for diagnosis and treatment of skin cancer. In this study, we investigate the utility of a dermatolog…
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…
Variational U-Net with Local Alignment for Joint Tumor Extraction and Registration (VALOR-Net) of Breast MRI Data Acquired at Two Different Field Strengths
Muhammad Shahkar Khan, Haider Ali, Laura Villazan Garcia +5
Background: Multiparametric breast MRI data might improve tumor diagnostics, characterization, and treatment planning. Accurate alignment and delineation of images acquired at diff…