27 citations · 57 across the 13 of their papers we have counts for
15 papers
From Density to Biopsy Decisions and Malignancy Prediction: A Benchmark Study of Multimodal Large Language Models Against Radiologists in Digital and Contrast-Enhanced Mammography
Ali Abbasian Ardakani, Afshin Mohammadi, Taha Yusuf Kuzan +11
Purpose: To compare four multimodal large language models (MLLMs) with radiologists of varying expertise in breast density assessment, BI-RADS assessment, biopsy candidacy determin…
CBCT-IQ: A Publicly Available Annotated Cone-Beam CT Dataset for Image Quality Assessment and Benchmarking
Sepideh Hatamikia, Anna Breger, Clemens Karner +14
Medical image quality plays a critical role in diagnostic accuracy, especially in X-ray-based imaging modalities such as cone-beam computed tomography (CBCT), where image quality m…
A deep learning pipeline for PAM50 subtype classification using histopathology images and multi-objective patch selection
Arezoo Borji, Gernot Kronreif, Bernhard Angermayr +6
Breast cancer is a highly heterogeneous disease with diverse molecular profiles. The PAM50 gene signature is widely recognized as a standard for classifying breast cancer into intr…
Deep learning based Non-Rigid Volume-to-Surface Registration for Brain Shift compensation Using Point Cloud
Eashrat Jahan Muniya, Gernot Kronreif, Ander Biguri +2
Soft-tissue deformation remains a major limitation in image-guided neurosurgery, where intra-operative anatomy can deviate substantially from pre-operative imaging due to brain shi…
No-reference based automatic parameter optimization for iterative reconstruction using a novel search space aware crow search algorithm
Poorya MohammadiNasab, Ander Biguri, Philipp Steininger +9
Iterative reconstruction technique's ability to reduce radiation exposure by using fewer projections has attracted significant attention. However, these methods typically require a…
An Integrated Optimization and Deep Learning Pipeline for Predicting Live Birth Success in IVF Using Feature Optimization and Transformer-Based Models
Arezoo Borji, Hossam Haick, Birgit Pohn +7
In vitro fertilization (IVF) is a widely utilized assisted reproductive technology, yet predicting its success remains challenging due to the multifaceted interplay of clinical, de…
A Review on the Integration of Artificial Intelligence and Medical Imaging in IVF Ovarian Stimulation
Jana Zakall, Birgit Pohn, Antonia Graf +6
Artificial intelligence (AI) has emerged as a powerful tool to enhance decision-making and optimize treatment protocols in in vitro fertilization (IVF). In particular, AI shows sig…
TIGRE v3: Efficient and easy to use iterative computed tomographic reconstruction toolbox for real datasets
Ander Biguri, Tomoyuki Sadakane, Reuben Lindroos +11
Computed Tomography (CT) has been widely adopted in medicine and it is increasingly being used in scientific and industrial applications. Parallelly, research in different mathemat…
Advanced Hybrid Deep Learning Model for Enhanced Classification of Osteosarcoma Histopathology Images
Arezoo Borji, Gernot Kronreif, Bernhard Angermayr +1
Recent advances in machine learning are transforming medical image analysis, particularly in cancer detection and classification. Techniques such as deep learning, especially convo…
A study of why we need to reassess full reference image quality assessment with medical images
Anna Breger, Ander Biguri, Malena Sabaté Landman +11
Image quality assessment (IQA) is indispensable in clinical practice to ensure high standards, as well as in the development stage of machine learning algorithms that operate on me…
Improving Generalization Capability of Deep Learning-Based Nuclei Instance Segmentation by Non-deterministic Train Time and Deterministic Test Time Stain Normalization
Amirreza Mahbod, Georg Dorffner, Isabella Ellinger +2
With the advent of digital pathology and microscopic systems that can scan and save whole slide histological images automatically, there is a growing trend to use computerized meth…
NuInsSeg: A Fully Annotated Dataset for Nuclei Instance Segmentation in H&E-Stained Histological Images
Amirreza Mahbod, Christine Polak, Katharina Feldmann +6
In computational pathology, automatic nuclei instance segmentation plays an essential role in whole slide image analysis. While many computerized approaches have been proposed for…
Silicone phantoms fabricated with multi-material extrusion 3D printing technology mimicking imaging properties of soft tissues in CT
Sepideh Hatamikia, Laszlo Jaksa, Gernot Kronreif +4
Recently, 3D printing has been widely used to fabricate medical imaging phantoms. So far, various rigid 3D printable materials have been investigated for their radiological propert…
Realistic 3D printed imaging tumor phantoms for validation of image processing algorithms
Sepideh Hatamikia, Ingo Gulyas, Wolfgang Birkfellner +11
Medical imaging phantoms are widely used for validation and verification of imaging systems and algorithms in surgical guidance and radiation oncology procedures. Especially, for t…
On Krylov Methods for Large Scale CBCT Reconstruction
Malena Sabate Landman, Ander Biguri, Sepideh Hatamikia +3
Krylov subspace methods are a powerful family of iterative solvers for linear systems of equations, which are commonly used for inverse problems due to their intrinsic regularizati…