no code implementations • 18 Oct 2024 • Cynthia Maldonado-Garcia, Arezoo Zakeri, Alejandro F Frangi, Nishant Ravikumar
This study demonstrates the potential of retinal optical coherence tomography (OCT) imaging combined with fundus photographs for identifying future adverse cardiac events.
1 code implementation • 26 Mar 2024 • Cynthia Maldonado-Garcia, Rodrigo Bonazzola, Enzo Ferrante, Thomas H Julian, Panagiotis I Sergouniotis, Nishant Ravikumara, Alejandro F Frangi
In this study, we investigated the potential of OCT as an additional imaging technique to predict future CVD events.
no code implementations • 18 Nov 2023 • Nurbanu Aksoy, Nishant Ravikumar, Alejandro F Frangi
While recent deep-learning approaches for automated report generation from medical images have seen some success, most studies have relied on image-derived features alone, ignoring non-imaging patient data.
no code implementations • 18 Nov 2023 • Nurbanu Aksoy, Serge Sharoff, Selcuk Baser, Nishant Ravikumar, Alejandro F Frangi
Image-to-text radiology report generation aims to automatically produce radiology reports that describe the findings in medical images.
no code implementations • 11 Aug 2023 • Karim Lekadir, Aasa Feragen, Abdul Joseph Fofanah, Alejandro F Frangi, Alena Buyx, Anais Emelie, Andrea Lara, Antonio R Porras, An-Wen Chan, Arcadi Navarro, Ben Glocker, Benard O Botwe, Bishesh Khanal, Brigit Beger, Carol C Wu, Celia Cintas, Curtis P Langlotz, Daniel Rueckert, Deogratias Mzurikwao, Dimitrios I Fotiadis, Doszhan Zhussupov, Enzo Ferrante, Erik Meijering, Eva Weicken, Fabio A González, Folkert W Asselbergs, Fred Prior, Gabriel P Krestin, Gary Collins, Geletaw S Tegenaw, Georgios Kaissis, Gianluca Misuraca, Gianna Tsakou, Girish Dwivedi, Haridimos Kondylakis, Harsha Jayakody, Henry C Woodruf, Horst Joachim Mayer, Hugo JWL Aerts, Ian Walsh, Ioanna Chouvarda, Irène Buvat, Isabell Tributsch, Islem Rekik, James Duncan, Jayashree Kalpathy-Cramer, Jihad Zahir, Jinah Park, John Mongan, Judy W Gichoya, Julia A Schnabel, Kaisar Kushibar, Katrine Riklund, Kensaku MORI, Kostas Marias, Lameck M Amugongo, Lauren A Fromont, Lena Maier-Hein, Leonor Cerdá Alberich, Leticia Rittner, Lighton Phiri, Linda Marrakchi-Kacem, Lluís Donoso-Bach, Luis Martí-Bonmatí, M Jorge Cardoso, Maciej Bobowicz, Mahsa Shabani, Manolis Tsiknakis, Maria A Zuluaga, Maria Bielikova, Marie-Christine Fritzsche, Marina Camacho, Marius George Linguraru, Markus Wenzel, Marleen de Bruijne, Martin G Tolsgaard, Marzyeh Ghassemi, Md Ashrafuzzaman, Melanie Goisauf, Mohammad Yaqub, Mónica Cano Abadía, Mukhtar M E Mahmoud, Mustafa Elattar, Nicola Rieke, Nikolaos Papanikolaou, Noussair Lazrak, Oliver Díaz, Olivier Salvado, Oriol Pujol, Ousmane Sall, Pamela Guevara, Peter Gordebeke, Philippe Lambin, Pieta Brown, Purang Abolmaesumi, Qi Dou, Qinghua Lu, Richard Osuala, Rose Nakasi, S Kevin Zhou, Sandy Napel, Sara Colantonio, Shadi Albarqouni, Smriti Joshi, Stacy Carter, Stefan Klein, Steffen E Petersen, Susanna Aussó, Suyash Awate, Tammy Riklin Raviv, Tessa Cook, Tinashe E M Mutsvangwa, Wendy A Rogers, Wiro J Niessen, Xènia Puig-Bosch, Yi Zeng, Yunusa G Mohammed, Yves Saint James Aquino, Zohaib Salahuddin, Martijn P A Starmans
This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare.
1 code implementation • 7 Aug 2023 • Fengming Lin, Yan Xia, Nishant Ravikumar, Qiongyao Liu, Michael MacRaild, Alejandro F Frangi
Accurate segmentation of brain vessels is crucial for cerebrovascular disease diagnosis and treatment.
no code implementations • 6 Feb 2023 • Rachael Harkness, Alejandro F Frangi, Kieran Zucker, Nishant Ravikumar
We generate visual examples to show that our explainability method, when applied to the trained DirVAE, is able to highlight regions in CXR images that are clinically relevant to the class(es) of interest and additionally, can identify cases where classification relies on spurious feature correlations.
no code implementations • 7 Jan 2023 • Rodrigo Bonazzola, Enzo Ferrante, Nishant Ravikumar, Yan Xia, Bernard Keavney, Sven Plein, Tanveer Syeda-Mahmood, Alejandro F Frangi
Here, we propose a new framework for gene discovery entitled Unsupervised Phenotype Ensembles (UPE).
1 code implementation • 24 Nov 2022 • Xiang Chen, Yan Xia, Nishant Ravikumar, Alejandro F Frangi
In such scenarios, enforcing smooth, globally continuous deformation fields leads to incorrect/implausible registration results.
1 code implementation • 14 Sep 2021 • Rachael Harkness, Geoff Hall, Alejandro F Frangi, Nishant Ravikumar, Kieran Zucker
Model performance results have been exceptional when training and testing on open-source data, surpassing the reported capabilities of AI in pneumonia-detection prior to the COVID-19 outbreak.
no code implementations • 2 Aug 2021 • Yuhao Huang, Xin Yang, Yuxin Zou, Chaoyu Chen, Jian Wang, Haoran Dou, Nishant Ravikumar, Alejandro F Frangi, Jianqiao Zhou, Dong Ni
Weakly-supervised segmentation (WSS) can help reduce time-consuming and cumbersome manual annotation.
no code implementations • 1 Aug 2021 • Zhendong Liu, Van Manh, Xin Yang, Xiaoqiong Huang, Karim Lekadir, Víctor Campello, Nishant Ravikumar, Alejandro F Frangi, Dong Ni
A style transfer model with style fusion is employed to generate the curriculum samples.
no code implementations • 31 Jul 2021 • Mingyuan Luo, Xin Yang, Xiaoqiong Huang, Yuhao Huang, Yuxin Zou, Xindi Hu, Nishant Ravikumar, Alejandro F Frangi, Dong Ni
In this paper, we propose a novel approach to sensorless freehand 3D US reconstruction considering the complex skill sequences.
1 code implementation • 9 Jul 2021 • Xiang Chen, Nishant Ravikumar, Yan Xia, Alejandro F Frangi
Image registration aims to establish spatial correspondence across pairs, or groups of images, and is a cornerstone of medical image computing and computer-assisted-interventions.
no code implementations • 11 Jun 2021 • Xiang Chen, Yan Xia, Nishant Ravikumar, Alejandro F Frangi
Image registration is a fundamental building block for various applications in medical image analysis.
no code implementations • 11 Jan 2021 • Zhendong Liu, Xiaoqiong Huang, Xin Yang, Rui Gao, Rui Li, Yuanji Zhang, Yankai Huang, Guangquan Zhou, Yi Xiong, Alejandro F Frangi, Dong Ni
Deep segmentation models that generalize to images with unknown appearance are important for real-world medical image analysis.