1.3k citations · 1.9k across the 80 of their papers we have counts for
90 papers
HemaHier: Chain-Conditioned Ordinal Hierarchies for Lineage-Aware Bone-Marrow Cytology
Afshin Bozorgpour, Peter Schüffler, Edgar Jost +1
Bone-marrow cytology is inherently structured: each cell belongs to a hematopoietic lineage, and many cell types lie on ordered maturation trajectories. Standard flat classifiers i…
Fast and Accurate Monomodal 3D High Resolution Deep Registration of Drosophila Larval Brain Volumes
Daniel Reisenbüchler, Yousef Sadegheih, Michael Dittrich +3
The larval stage of Drosophila melanogaster is a compact model system for neuroscience whose genetic toolkit allows fluorescent markers to be expressed in defined neural population…
TRIUNE-Net: Harmonizing Scale, Shape, and Efficiency in Pancreatic Tumor Segmentation
Amir Hossein Saleknia, Alireza Kheyrkhah, Sanaz Karimijafarbigloo +5
Pancreatic tumor segmentation in 3D CT volumes is challenged by extreme scale variability across both the pancreas and tumor, and highly irregular tumor morphology. While recent ad…
MaLViL: Multi-axis Low-rank Vision-LSTM for Medical Image Segmentation
Afshin Bozorgpour, Sina Ghorbani Kolahi, Moein Heidari +2
Vision-LSTM (ViL) enables efficient global modeling, but its cost still scales with the number of spatial tokens, so existing segmenters confine ViL to a coarse bottleneck and lose…
Spatial Masked-Set Learning for Sparse Multi-Shell Diffusion MRI Signal Synthesis
Yousef Sadegheih, Pratibha Kumari, Dorit Merhof
Dense multi-shell diffusion MRI provides rich q-space information but requires long acquisition times. We propose a spatial masked-set framework for sparse multi-shell diffusion MR…
Approximate Attention Weighting for Sustainable FPGA-Based Vision Transformer Inference
Muhammad Usman, Muhammad Akmal Shafique, Shujaat Khan +1
Vision Transformers have reshaped computer vision by using self-attention to capture global context across image regions. This makes them attractive for edge visual inspection and…
MINT: Dynamic-Precision CNN Inference with MSDF Digit-Serial Arithmetic on FPGA
Muhammad Usman, Malik Zohaib Nisar, Florian Aschauer +1
We present MINT, a dynamic-precision CNN inference accelerator based on left-to-right (LR) arithmetic. LR arithmetic computes in most-significant-digit-first manner and exposes use…
Dynamic Ultrasound Beamforming Using Left-to-Right Arithmetic Adders on FPGA
Muhammad Usman, Shujaat Khan, Dorit Merhof
Adder trees are the computational backbone of delay-and-sum (DAS) ultrasound beamforming, where their implementation directly determines the energy, throughput, and area of a real-…
Energy-Efficient CNN Acceleration with MSDF Digit-Serial Arithmetic on FPGA
Muhammad Usman, Yousef Sadegheih, Dorit Merhof
This paper presents an energy-efficient hardware acceleration of the convolutional layers in the U-Net architecture for image segmentation, implemented on FPGA. While digit-serial…
Harmonized Feature Conditioning and Frequency-Prompt Personalization for Multi-Rater Medical Segmentation
Sanaz Karimijafarbigloo, Armin Khosravi, Alireza Kheyrkhah +3
Multi-rater medical image segmentation captures the inherent ambiguity of clinical interpretation, where diagnostic boundaries vary across experts and imaging devices. Existing app…
Gated Differential Linear Attention: A Linear-Time Decoder for High-Fidelity Medical Segmentation
Hongbo Zheng, Afshin Bozorgpour, Dorit Merhof +1
Medical image segmentation requires models that preserve fine anatomical boundaries while remaining practical for clinical deployment. Transformers capture long-range dependencies…
Footprint-Guided Exemplar-Free Continual Histopathology Report Generation
Pratibha Kumari, Daniel Reisenbüchler, Afshin Bozorgpour +3
Rapid progress in vision-language modeling has enabled pathology report generation from gigapixel whole-slide images, but most approaches assume static training with simultaneous a…
Towards Modality-Agnostic Continual Domain-Incremental Brain Lesion Segmentation
Yousef Sadegheih, Dorit Merhof, Pratibha Kumari
Brain lesion segmentation from multi-modal MRI often assumes fixed modality sets or predefined pathologies, making existing models difficult to adapt across cohorts and imaging pro…
Tissue Classification and Whole-Slide Images Analysis via Modeling of the Tumor Microenvironment and Biological Pathways
Junzhuo Liu, Xuemei Du, Daniel Reisenbuchler +5
Automatic integration of whole slide images (WSIs) and gene expression profiles has demonstrated substantial potential in precision clinical diagnosis and cancer progression studie…
Deep Learning-Based Desikan-Killiany Parcellation of the Brain Using Diffusion MRI
Yousef Sadegheih, Dorit Merhof
Accurate brain parcellation in diffusion MRI (dMRI) space is essential for advanced neuroimaging analyses. However, most existing approaches rely on anatomical MRI for segmentation…
Spatial Transcriptomics Expression Prediction from Histopathology Based on Cross-Modal Mask Reconstruction and Contrastive Learning
Junzhuo Liu, Markus Eckstein, Zhixiang Wang +2
Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling…
CENet: Context Enhancement Network for Medical Image Segmentation
Afshin Bozorgpour, Sina Ghorbani Kolahi, Reza Azad +2
Medical image segmentation, particularly in multi-domain scenarios, requires precise preservation of anatomical structures across diverse representations. While deep learning has a…
Attention-based Generative Latent Replay: A Continual Learning Approach for WSI Analysis
Pratibha Kumari, Daniel Reisenbüchler, Afshin Bozorgpour +3
Whole slide image (WSI) classification has emerged as a powerful tool in computational pathology, but remains constrained by domain shifts, e.g., due to different organs, diseases,…
Towards Robust and Generalizable Gerchberg Saxton based Physics Inspired Neural Networks for Computer Generated Holography: A Sensitivity Analysis Framework
Ankit Amrutkar, Björn Kampa, Volkmar Schulz +3
Computer-generated holography (CGH) enables applications in holographic augmented reality (AR), 3D displays, systems neuroscience, and optical trapping. The fundamental challenge i…
Domain-incremental White Blood Cell Classification with Privacy-aware Continual Learning
Pratibha Kumari, Afshin Bozorgpour, Daniel Reisenbüchler +4
White blood cell (WBC) classification plays a vital role in hematology for diagnosing various medical conditions. However, it faces significant challenges due to domain shifts caus…
Modality-Agnostic Brain Lesion Segmentation with Privacy-aware Continual Learning
Yousef Sadegheih, Pratibha Kumari, Dorit Merhof
Traditional brain lesion segmentation models for multi-modal MRI are typically tailored to specific pathologies, relying on datasets with predefined modalities. Adapting to new MRI…
Echo-ENet: Efficient Endocardial Spatio-Temporal Network for Ejection Fraction Estimation
Moein Heidari, Afshin Bozorgpour, AmirHossein Zarif-Fakharnia +6
Left ventricular ejection fraction (LVEF) is a primary marker of cardiac function. However, routine estimation from endocardial measurements requires manual delineation at end-dias…
Touchstone Benchmark: Are We on the Right Way for Evaluating AI Algorithms for Medical Segmentation?
Pedro R. A. S. Bassi, Wenxuan Li, Yucheng Tang +50
How can we test AI performance? This question seems trivial, but it isn't. Standard benchmarks often have problems such as in-distribution and small-size test sets, oversimplified…
Continual Domain Incremental Learning for Privacy-aware Digital Pathology
Pratibha Kumari, Daniel Reisenbüchler, Lucas Luttner +3
In recent years, there has been remarkable progress in the field of digital pathology, driven by the ability to model complex tissue patterns using advanced deep-learning algorithm…