39 citations · 73 across the 14 of their papers we have counts for
14 papers
Pre- to Post-Contrast Synthesis of Breast DCE-MRI using Latent Bridge Matching
Sina Amirrajab, Zohaib Salahuddin, Henry C Woodruff +1
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is central to breast cancer imaging, but gadolinium administration increases scan burden and motivates contrast-reduc…
Robust Multicentre Detection and Classification of Colorectal Liver Metastases on CT: Application of Foundation Models
Shruti Atul Mali, Zohaib Salahuddin, Yumeng Zhang +10
Colorectal liver metastases (CRLM) are a major cause of cancer-related mortality, and reliable detection on CT remains challenging in multi-centre settings. We developed a foundati…
Radiology Report Conditional 3D CT Generation with Multi Encoder Latent diffusion Model
Sina Amirrajab, Zohaib Salahuddin, Sheng Kuang +2
Text to image latent diffusion models have recently advanced medical image synthesis, but applications to 3D CT generation remain limited. Existing approaches rely on simplified pr…
Explainable Anatomy-Guided AI for Prostate MRI: Foundation Models and In Silico Clinical Trials for Virtual Biopsy-based Risk Assessment
Danial Khan, Zohaib Salahuddin, Yumeng Zhang +11
We present a fully automated, anatomically guided deep learning pipeline for prostate cancer (PCa) risk stratification using routine MRI. The pipeline integrates three key componen…
A Pre-trained Foundation Model Framework for Multiplanar MRI Classification of Extramural Vascular Invasion and Mesorectal Fascia Invasion in Rectal Cancer
Yumeng Zhang, Shruti Atul Mali, Danial Khan +10
Objectives Accurate MRI-based identification of extramural vascular invasion (EVI) and mesorectal fascia invasion (MFI) is crucial for risk-stratified rectal cancer treatment. Howe…
Consensus in the Parliament of AI: Harmonized Multi-Region CT-Radiomics and Foundation-Model Signatures for Multicentre NSCLC Risk Stratification
Shruti Atul Mali, Zohaib Salahuddin, Danial Khan +13
Purpose: This study evaluates the impact of harmonization and multi-region feature integration on survival prediction in non-small cell lung cancer (NSCLC) patients. We assess the…
Methodological Explainability Evaluation of an Interpretable Deep Learning Model for Post-Hepatectomy Liver Failure Prediction Incorporating Counterfactual Explanations and Layerwise Relevance Propagation: A Prospective In Silico Trial
Xian Zhong, Zohaib Salahuddin, Yi Chen +15
Artificial intelligence (AI)-based decision support systems have demonstrated value in predicting post-hepatectomy liver failure (PHLF) in hepatocellular carcinoma (HCC). However,…
Counterfactuals and Uncertainty-Based Explainable Paradigm for the Automated Detection and Segmentation of Renal Cysts in Computed Tomography Images: A Multi-Center Study
Zohaib Salahuddin, Abdalla Ibrahim, Sheng Kuang +10
Routine computed tomography (CT) scans often detect a wide range of renal cysts, some of which may be malignant. Early and precise localization of these cysts can significantly aid…
FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare
Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah +117
Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. I…
Precision-medicine-toolbox: An open-source python package for facilitation of quantitative medical imaging and radiomics analysis
Sergey Primakov, Elizaveta Lavrova, Zohaib Salahuddin +2
Medical image analysis plays a key role in precision medicine as it allows the clinicians to identify anatomical abnormalities and it is routinely used in clinical assessment. Data…
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods
Zohaib Salahuddin, Henry C Woodruff, Avishek Chatterjee +1
Artificial Intelligence has emerged as a useful aid in numerous clinical applications for diagnosis and treatment decisions. Deep neural networks have shown same or better performa…
FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging
Karim Lekadir, Richard Osuala, Catherine Gallin +13
The recent advancements in artificial intelligence (AI) combined with the extensive amount of data generated by today's clinical systems, has led to the development of imaging AI s…
Leveraging SLIC Superpixel Segmentation and Cascaded Ensemble SVM for Fully Automated Mass Detection In Mammograms
Jaime Simarro, Zohaib Salahuddin, Ahmed Gouda +1
Identification and segmentation of breast masses in mammograms face complex challenges, owing to the highly variable nature of malignant densities with regards to their shape, cont…
Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans
Zohaib Salahuddin, Matthias Lenga, Hannes Nickisch
We propose a deep learning-based automatic coronary artery tree centerline tracker (AuCoTrack) extending the vessel tracker by Wolterink (arXiv:1810.03143). A dual pathway Convolut…