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Full-Text Articles in Medicine and Health Sciences
A Multi-Institutional Meningioma Mri Dataset For Automated Multi-Sequence Image Segmentation, Dominic Labella, Omaditya Khanna, Shan Mcburney-Lin, Ryan Mclean, Pierre Nedelec, Arif Rashid, Nourel Hoda Tahon, Talissa Altes, Ujjwal Baid, Radhika Bhalerao, Yaseen Dhemesh, Scott Floyd, Devon Godfrey, Fathi Hilal, Anastasia Janas, Anahita Kazerooni, Collin Kent, John Kirkpatrick, Florian Kofler, Kevin Leu, Nazanin Maleki, Bjoern Menze, Maxence Pajot, Zachary Reitman, Jeffrey Rudie, Rachit Saluja, Yury Velichko, Chunhao Wang, Pranav Warman, Nico Sollmann, David Diffley, Khanak Nandolia, Daniel Warren, Ali Hussain, John Pascal Fehringer, Yulia Bronstein, Lisa Deptula, Evan Stein, Mahsa Taherzadeh, Eduardo Portela De Oliveira, Aoife Haughey, Marinos Kontzialis, Luca Saba, Benjamin Turner, Melanie Brüßeler, Shehbaz Ansari, Athanasios Gkampenis, David Maximilian Weiss, Aya Mansour, Islam Shawali, Nikolay Yordanov, Joel Stein, Roula Hourani, Mohammed Yahya Moshebah, Ahmed Magdy Abouelatta, Tanvir Rizvi, Klara Willms, Dann Martin, Abdullah Okar, Gennaro D'Anna, Ahmed Taha, Yasaman Sharifi, Shahriar Faghani, Dominic Kite, Marco Pinho, Muhammad Ammar Haider, Michelle Alonso-Basanta, Javier Villanueva-Meyer, Andreas Rauschecker, Ayman Nada, Mariam Aboian, Adam Flanders, Spyridon Bakas, Evan Calabrese
A Multi-Institutional Meningioma Mri Dataset For Automated Multi-Sequence Image Segmentation, Dominic Labella, Omaditya Khanna, Shan Mcburney-Lin, Ryan Mclean, Pierre Nedelec, Arif Rashid, Nourel Hoda Tahon, Talissa Altes, Ujjwal Baid, Radhika Bhalerao, Yaseen Dhemesh, Scott Floyd, Devon Godfrey, Fathi Hilal, Anastasia Janas, Anahita Kazerooni, Collin Kent, John Kirkpatrick, Florian Kofler, Kevin Leu, Nazanin Maleki, Bjoern Menze, Maxence Pajot, Zachary Reitman, Jeffrey Rudie, Rachit Saluja, Yury Velichko, Chunhao Wang, Pranav Warman, Nico Sollmann, David Diffley, Khanak Nandolia, Daniel Warren, Ali Hussain, John Pascal Fehringer, Yulia Bronstein, Lisa Deptula, Evan Stein, Mahsa Taherzadeh, Eduardo Portela De Oliveira, Aoife Haughey, Marinos Kontzialis, Luca Saba, Benjamin Turner, Melanie Brüßeler, Shehbaz Ansari, Athanasios Gkampenis, David Maximilian Weiss, Aya Mansour, Islam Shawali, Nikolay Yordanov, Joel Stein, Roula Hourani, Mohammed Yahya Moshebah, Ahmed Magdy Abouelatta, Tanvir Rizvi, Klara Willms, Dann Martin, Abdullah Okar, Gennaro D'Anna, Ahmed Taha, Yasaman Sharifi, Shahriar Faghani, Dominic Kite, Marco Pinho, Muhammad Ammar Haider, Michelle Alonso-Basanta, Javier Villanueva-Meyer, Andreas Rauschecker, Ayman Nada, Mariam Aboian, Adam Flanders, Spyridon Bakas, Evan Calabrese
Department of Radiology Faculty Papers
Meningiomas are the most common primary intracranial tumors and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists, and radiation oncologists rely on brain MRI for diagnosis, treatment planning, and longitudinal treatment monitoring. However, automated, objective, and quantitative tools for non-invasive assessment of meningiomas on multi-sequence MR images are not available. Here we present the BraTS Pre-operative Meningioma Dataset, as the largest multi-institutional expert annotated multilabel meningioma multi-sequence MR image dataset to date. This dataset includes 1,141 multi-sequence MR images from six sites, each with four structural MRI sequences (T2-, T2/FLAIR-, pre-contrast T1-, and post-contrast T1-weighted) accompanied by …
Harmonization Of Multi-Site Diffusion Tensor Imaging Data For Cervical And Thoracic Spinal Cord At 1.5 T And 3 T Using Longitudinal Combat, Devon M. Middleton, Yutong Li, Andrew Chen, Russell Shinohara, Joshua Fisher, Laura Krisa, Mark Elliot, Scott H. Faro, John H. Woo, Adam E. Flanders, Feroze B. Mohamed
Harmonization Of Multi-Site Diffusion Tensor Imaging Data For Cervical And Thoracic Spinal Cord At 1.5 T And 3 T Using Longitudinal Combat, Devon M. Middleton, Yutong Li, Andrew Chen, Russell Shinohara, Joshua Fisher, Laura Krisa, Mark Elliot, Scott H. Faro, John H. Woo, Adam E. Flanders, Feroze B. Mohamed
Department of Radiology Faculty Papers
MRI scanner hardware, field strengths, and sequence parameters are major variables in diffusion studies of the spinal cord. Reliability between scanners is not well known, particularly for the thoracic cord. DTI data was collected for the entire cervical and thoracic spinal cord in thirty healthy adult subjects with different MR vendors and field strengths. DTI metrics were extracted and averaged for all slices within each vertebral level. Metrics were examined for variability and then harmonized using longitudinal ComBat (longComBat). Four scanners were used: Siemens 3 T Prisma, Siemens 1.5 T Avanto, Philips 3 T Ingenia, Philips 1.5 T Achieva. Average …