Search Results for author: Zohaib Salahuddin

Found 5 papers, 1 papers with code

Precision-medicine-toolbox: An open-source python package for facilitation of quantitative medical imaging and radiomics analysis

1 code implementation28 Feb 2022 Sergey Primakov, Elizaveta Lavrova, Zohaib Salahuddin, Henry C Woodruff, Philippe Lambin

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.

Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods

no code implementations1 Nov 2021 Zohaib Salahuddin, Henry C Woodruff, Avishek Chatterjee, Philippe Lambin

Artificial Intelligence has emerged as a useful aid in numerous clinical applications for diagnosis and treatment decisions.

Decision Making

FUTURE-AI: Guiding Principles and Consensus Recommendations for Trustworthy Artificial Intelligence in Medical Imaging

no code implementations20 Sep 2021 Karim Lekadir, Richard Osuala, Catherine Gallin, Noussair Lazrak, Kaisar Kushibar, Gianna Tsakou, Susanna Aussó, Leonor Cerdá Alberich, Kostas Marias, Manolis Tsiknakis, Sara Colantonio, Nickolas Papanikolaou, Zohaib Salahuddin, Henry C Woodruff, Philippe Lambin, Luis Martí-Bonmatí

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 solutions across the whole value chain of medical imaging, including image reconstruction, medical image segmentation, image-based diagnosis and treatment planning.

Fairness Image Reconstruction +2

Leveraging SLIC Superpixel Segmentation and Cascaded Ensemble SVM for Fully Automated Mass Detection In Mammograms

no code implementations20 Oct 2020 Jaime Simarro, Zohaib Salahuddin, Ahmed Gouda, Anindo Saha

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, contours, texture and orientation.

Multi-Resolution 3D Convolutional Neural Networks for Automatic Coronary Centerline Extraction in Cardiac CT Angiography Scans

no code implementations2 Oct 2020 Zohaib Salahuddin, Matthias Lenga, Hannes Nickisch

A similar multi-scale dual pathway 3D CNN is trained to identify coronary artery endpoints for terminating the tracking process.

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