31 citations · 92 across the 21 of their papers we have counts for
13 papers · 1 filter
Exploring the Effectiveness of Deep Features from Domain-Specific Foundation Models in Retinal Image Synthesis
Zuzanna Skorniewska, Bartlomiej W. Papiez
The adoption of neural network models in medical imaging has been constrained by strict privacy regulations, limited data availability, high acquisition costs, and demographic bias…
Rethinking Foundation Models for Medical Image Classification through a Benchmark Study on MedMNIST
Fuping Wu, Bartlomiej W. Papiez
Foundation models are widely employed in medical image analysis, due to their high adaptability and generalizability for downstream tasks. With the increasing number of foundation…
KneeXNeT: An Ensemble-Based Approach for Knee Radiographic Evaluation
Nicharee Srikijkasemwat, Soumya Snigdha Kundu, Fuping Wu +1
Knee osteoarthritis (OA) is the most common joint disorder and a leading cause of disability. Diagnosing OA severity typically requires expert assessment of X-ray images and is com…
SpineFM: Leveraging Foundation Models for Automatic Spine X-ray Segmentation
Samuel J. Simons, Bartłomiej W. Papież
This paper introduces SpineFM, a novel pipeline that achieves state-of-the-art performance in the automatic segmentation and identification of vertebral bodies in cervical and lumb…
Deformation-Recovery Diffusion Model (DRDM): Instance Deformation for Image Manipulation and Synthesis
Jian-Qing Zheng, Yuanhan Mo, Yang Sun +5
In medical imaging, the diffusion models have shown great potential for synthetic image generation tasks. However, these approaches often lack the interpretable connections between…
Deep Learning Models to Automate the Scoring of Hand Radiographs for Rheumatoid Arthritis
Zhiyan Bo, Laura C. Coates, Bartlomiej W. Papiez
The van der Heijde modification of the Sharp (SvdH) score is a widely used radiographic scoring method to quantify damage in Rheumatoid Arthritis (RA) in clinical trials. However,…
Paired Diffusion: Generation of related, synthetic PET-CT-Segmentation scans using Linked Denoising Diffusion Probabilistic Models
Rowan Bradbury, Katherine A. Vallis, Bartlomiej W. Papiez
The rapid advancement of Artificial Intelligence (AI) in biomedical imaging and radiotherapy is hindered by the limited availability of large imaging data repositories. With recent…
Prediction of recurrence free survival of head and neck cancer using PET/CT radiomics and clinical information
Mona Furukawa, Daniel R. McGowan, Bartłomiej W. Papież
The 5-year survival rate of Head and Neck Cancer (HNC) has not improved over the past decade and one common cause of treatment failure is recurrence. In this paper, we built Cox pr…
VertXNet: An Ensemble Method for Vertebrae Segmentation and Identification of Spinal X-Ray
Yao Chen, Yuanhan Mo, Aimee Readie +5
Reliable vertebrae annotations are key to perform analysis of spinal X-ray images. However, obtaining annotation of vertebrae from those images is usually carried out manually due…
VertXNet: Automatic Segmentation and Identification of Lumbar and Cervical Vertebrae from Spinal X-ray Images
Yao Chen, Yuanhan Mo, Aimee Readie +3
Manual annotation of vertebrae on spinal X-ray imaging is costly and time-consuming due to bone shape complexity and image quality variations. In this study, we address this challe…
Residual Aligner Network
Jian-Qing Zheng, Ziyang Wang, Baoru Huang +2
Image registration is important for medical imaging, the estimation of the spatial transformation between different images. Many previous studies have used learning-based methods f…
D-Net: Siamese based Network with Mutual Attention for Volume Alignment
Jian-Qing Zheng, Ngee Han Lim, Bartlomiej W. Papiez
Alignment of contrast and non-contrast-enhanced imaging is essential for the quantification of changes in several biomedical applications. In particular, the extraction of cartilag…
Automated fetal brain extraction from clinical Ultrasound volumes using 3D Convolutional Neural Networks
Felipe Moser, Ruobing Huang, Aris T. Papageorghiou +2
To improve the performance of most neuroimiage analysis pipelines, brain extraction is used as a fundamental first step in the image processing. But in the case of fetal brain deve…