no code implementations • 22 Feb 2024 • Abhieet Parida, Daniel Capellan-Martin, Sara Atito, Muhammad Awais, Maria J. Ledesma-Carbayo, Marius G. Linguraru, Syed Muhammad Anwar
In this context, we introduce Diverse Concept Modeling (DiCoM), a novel self-supervised training paradigm that leverages a student teacher framework for learning diverse concepts and hence effective representation of the CXR data.
no code implementations • 6 Feb 2024 • Muhammad Mohsin Altaf, Saadat Ullah Khan, Muhammad Majd, Syed Muhammad Anwar
This paper presents an innovative approach to recognizing personality traits using deep learning (DL) methods applied to electrocardiogram (ECG) signals.
no code implementations • 21 Aug 2023 • Abhijeet Parida, Zhifan Jiang, Syed Muhammad Anwar, Nicholas Foreman, Nicholas Stence, Michael J. Fisher, Roger J. Packer, Robert A. Avery, Marius George Linguraru
To prevent hallucination in medical imaging, such as magnetic resonance images (MRI) of the brain, we propose a one-shot learning method where we utilize neural style transfer for harmonization.
no code implementations • 4 Jul 2023 • Sunder Ali Khowaja, Kapal Dev, Syed Muhammad Anwar, Marius George Linguraru
We perform our experimental analysis on publicly available medical imaging datasets and show that our proposed SelfFed framework performs better when compared to existing baselines concerning non-independent and identically distributed (IID) data and label scarcity.
no code implementations • 1 Jun 2023 • Ahmed W. Moawad, Anastasia Janas, Ujjwal Baid, Divya Ramakrishnan, Leon Jekel, Kiril Krantchev, Harrison Moy, Rachit Saluja, Klara Osenberg, Klara Wilms, Manpreet Kaur, Arman Avesta, Gabriel Cassinelli Pedersen, Nazanin Maleki, Mahdi Salimi, Sarah Merkaj, Marc von Reppert, Niklas Tillmans, Jan Lost, Khaled Bousabarah, Wolfgang Holler, MingDe Lin, Malte Westerhoff, Ryan Maresca, Katherine E. Link, Nourel Hoda Tahon, Daniel Marcus, Aristeidis Sotiras, Pamela Lamontagne, Strajit Chakrabarty, Oleg Teytelboym, Ayda Youssef, Ayaman Nada, Yuri S. Velichko, Nicolo Gennaro, Connectome Students, Group of Annotators, Justin Cramer, Derek R. Johnson, Benjamin Y. M. Kwan, Boyan Petrovic, Satya N. Patro, Lei Wu, Tiffany So, Gerry Thompson, Anthony Kam, Gloria Guzman Perez-Carrillo, Neil Lall, Group of Approvers, Jake Albrecht, Udunna Anazodo, Marius George Lingaru, Bjoern H Menze, Benedikt Wiestler, Maruf Adewole, Syed Muhammad Anwar, Dominic LaBella, Hongwei Bran Li, Juan Eugenio Iglesias, Keyvan Farahani, James Eddy, Timothy Bergquist, Verena Chung, Russel Takeshi Shinohara, Farouk Dako, Walter Wiggins, Zachary Reitman, Chunhao Wang, Xinyang Liu, Zhifan Jiang, Koen van Leemput, Marie Piraud, Ivan Ezhov, Elaine Johanson, Zeke Meier, Ariana Familiar, Anahita Fathi Kazerooni, Florian Kofler, Evan Calabrese, Sanjay Aneja, Veronica Chiang, Ichiro Ikuta, Umber Shafique, Fatima Memon, Gian Marco Conte, Spyridon Bakas, Jeffrey Rudie, Mariam Aboian
Clinical monitoring of metastatic disease to the brain can be a laborious and time-consuming process, especially in cases involving multiple metastases when the assessment is performed manually.
1 code implementation • 15 May 2023 • Florian Kofler, Felix Meissen, Felix Steinbauer, Robert Graf, Eva Oswald, Ezequiel de da Rosa, Hongwei Bran Li, Ujjwal Baid, Florian Hoelzl, Oezguen Turgut, Izabela Horvath, Diana Waldmannstetter, Christina Bukas, Maruf Adewole, Syed Muhammad Anwar, Anastasia Janas, Anahita Fathi Kazerooni, Dominic LaBella, Ahmed W Moawad, Keyvan Farahani, James Eddy, Timothy Bergquist, Verena Chung, Russell Takeshi Shinohara, Farouk Dako, Walter Wiggins, Zachary Reitman, Chunhao Wang, Xinyang Liu, Zhifan Jiang, Ariana Familiar, Gian-Marco Conte, Elaine Johanson, Zeke Meier, Christos Davatzikos, John Freymann, Justin Kirby, Michel Bilello, Hassan M Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Rivka R Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc-André Weber, Abhishek Mahajan, Suyash Mohan, John Mongan, Christopher Hess, Soonmee Cha, Javier Villanueva-Meyer, Errol Colak, Priscila Crivellaro, Andras Jakab, Jake Albrecht, Udunna Anazodo, Mariam Aboian, Juan Eugenio Iglesias, Koen van Leemput, Spyridon Bakas, Daniel Rueckert, Benedikt Wiestler, Ivan Ezhov, Marie Piraud, Bjoern Menze
The challenge is organized as part of the BraTS 2023 challenge hosted at the MICCAI 2023 conference in Vancouver, Canada.
no code implementations • 15 May 2023 • Hongwei Bran Li, Gian Marco Conte, Syed Muhammad Anwar, Florian Kofler, Ivan Ezhov, Koen van Leemput, Marie Piraud, Maria Diaz, Byrone Cole, Evan Calabrese, Jeff Rudie, Felix Meissen, Maruf Adewole, Anastasia Janas, Anahita Fathi Kazerooni, Dominic LaBella, Ahmed W. Moawad, Keyvan Farahani, Russell Takeshi Shinohara, Farouk Dako, Walter Wiggins, Zachary Reitman, Chunhao Wang, Xinyang Liu, Zhifan Jiang, Ariana Familiar, Elaine Johanson, Zeke Meier, Christos Davatzikos, John Freymann, Justin Kirby, Michel Bilello, Hassan M. Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Rivka R. Colen, Aikaterini Kotrotsou, Pamela Lamontagne, Daniel Marcus, Mikhail Milchenko, Arash Nazeri, Marc André Weber, Abhishek Mahajan, Suyash Mohan, John Mongan, Christopher Hess, Soonmee Cha, Javier Villanueva, Meyer Errol Colak, Priscila Crivellaro, Andras Jakab, Udunna Anazodo, Mariam Aboian, Thomas Yu, Verena Chung, Timothy Bergquist, James Eddy, Jake Albrecht, Ujjwal Baid, Spyridon Bakas, Marius George Linguraru, Bjoern Menze, Juan Eugenio Iglesias, Benedikt Wiestler
In this work, we present the establishment of the Brain MR Image Synthesis Benchmark (BraSyn) in conjunction with the Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2023.
no code implementations • 12 May 2023 • Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta, Talissa Altes, Syed Muhammad Anwar, Ujjwal Baid, Timothy Bergquist, Radhika Bhalerao, Sully Chen, Verena Chung, Gian-Marco Conte, Farouk Dako, James Eddy, Ivan Ezhov, Devon Godfrey, Fathi Hilal, Ariana Familiar, Keyvan Farahani, Juan Eugenio Iglesias, Zhifan Jiang, Elaine Johanson, Anahita Fathi Kazerooni, Collin Kent, John Kirkpatrick, Florian Kofler, Koen van Leemput, Hongwei Bran Li, Xinyang Liu, Aria Mahtabfar, Shan McBurney-Lin, Ryan McLean, Zeke Meier, Ahmed W Moawad, John Mongan, Pierre Nedelec, Maxence Pajot, Marie Piraud, Arif Rashid, Zachary Reitman, Russell Takeshi Shinohara, Yury Velichko, Chunhao Wang, Pranav Warman, Walter Wiggins, Mariam Aboian, Jake Albrecht, Udunna Anazodo, Spyridon Bakas, Adam Flanders, Anastasia Janas, Goldey Khanna, Marius George Linguraru, Bjoern Menze, Ayman Nada, Andreas M Rauschecker, Jeff Rudie, Nourel Hoda Tahon, Javier Villanueva-Meyer, Benedikt Wiestler, Evan Calabrese
Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality.
no code implementations • 1 Apr 2023 • Saadat Ullah Khan, Muhammad Majid, Syed Muhammad Anwar
We propose a method to classify four ME classes for different subjects using spectrograms of the EEG data through pre-trained deep learning (DL) models.
no code implementations • 23 Nov 2022 • Syed Muhammad Anwar, Abhijeet Parida, Sara Atito, Muhammad Awais, Gustavo Nino, Josef Kitler, Marius George Linguraru
However, the traditional diagnostic tool design methods based on supervised learning are burdened by the need to provide training data annotation, which should be of good quality for better clinical outcomes.
Ranked #1 on Semantic Segmentation on Montgomery County X-ray Set
no code implementations • 15 Nov 2022 • Saadat Ullah Khan, Muhammad Majid, Syed Muhammad Anwar
Our novel approach for the classification of upper limb movements using pre-trained DL algorithms and spectrograms has achieved significantly improved results for seven movement classes.
no code implementations • 29 Aug 2022 • Sara Atito, Syed Muhammad Anwar, Muhammad Awais, Josef Kitler
The availability of large scale data with high quality ground truth labels is a challenge when developing supervised machine learning solutions for healthcare domain.
no code implementations • 22 Jun 2022 • Muhammad Majid, Aamir Arsalan, Syed Muhammad Anwar
A perceived stress scale (PSS) questionnaire is used to record the stress of participants, which is then used to assign stress labels (two- and three classes).
no code implementations • 7 Feb 2022 • Aamir Arsalan, Muhammad Majid, Imran Fareed Nizami, Waleed Manzoor, Syed Muhammad Anwar, Jihyoung Ryu
This paper presents a comprehensive review of methods covering significant subjective and objective human stress detection techniques available in the literature.
no code implementations • 8 Apr 2021 • Maleeha Khalid Khan, Syed Muhammad Anwar
Our proposed model segments cup and disc regions based on which the abnormalities in cup to disc ratio can be observed.
no code implementations • 8 Jan 2021 • Ali Nawaz, Syed Muhammad Anwar, Rehan Liaqat, Javid Iqbal, Ulas Bagci, Muhammad Majid
Alzheimer's disease (AD) is a progressive and incurable neurodegenerative disease which destroys brain cells and causes loss to patient's memory.
no code implementations • 18 Oct 2020 • Harish RaviPrakash, Syed Muhammad Anwar, Ulas Bagci
We propose a novel capsule network based variational encoder architecture, called Bayesian capsules (B-Caps), to modulate the mean and standard deviation of the sampling distribution in the latent space.
no code implementations • 7 Sep 2020 • Sobia Yousaf, Syed Muhammad Anwar, Harish RaviPrakash, Ulas Bagci
Thus, accurate survival prognosis is an important step in treatment planning.
no code implementations • 1 Mar 2020 • Ismail Irmakci, Syed Muhammad Anwar, Drew A. Torigian, Ulas Bagci
The diagnosis, prognosis, and treatment of patients with musculoskeletal (MSK) disorders require radiology imaging (using computed tomography, magnetic resonance imaging(MRI), and ultrasound) and their precise analysis by expert radiologists.
no code implementations • 16 Oct 2019 • Syed Muhammad Anwar, Tooba Altaf, Khola Rafique, Harish RaviPrakash, Hassan Mohy-ud-Din, Ulas Bagci
Artificial intelligence (AI) enabled radiomics has evolved immensely especially in the field of oncology.
no code implementations • 17 Jul 2019 • Sanay Muhammad Umar Saeed, Syed Muhammad Anwar, Humaira Khalid, Muhammad Majid, Ulas Bagci
Stress research is a rapidly emerging area in thefield of electroencephalography (EEG) based signal processing. The use of EEG as an objective measure for cost effective andpersonalized stress management becomes important in particularsituations such as the non-availability of mental health facilities. In this study, long-term stress is classified using baseline EEGsignal recordings.
no code implementations • 13 May 2019 • Aasim Raheel, Muhammad Majid, Syed Muhammad Anwar, Ulas Bagci
The response to this enhanced multimedia content (mulsemedia) is evaluated in terms of the appreciation/emotion by using human brain signals.
no code implementations • 13 May 2019 • Aamir Arsalan, Muhammad Majid, Syed Muhammad Anwar, Ulas Bagci
In this paper, we present an experimental study for the classification of perceived human stress using non-invasive physiological signals.
no code implementations • 4 Sep 2017 • Syed Muhammad Anwar, Muhammad Majid, Adnan Qayyum, Muhammad Awais, Majdi Alnowami, Muhammad Khurram Khan
Deep learning is successfully used as a tool for machine learning, where a neural network is capable of automatically learning features.
no code implementations • 1 Aug 2017 • Saddam Hussain, Syed Muhammad Anwar, Muhammad Majid
A patch based approach along with an inception module is used for training the deep network by extracting two co-centric patches of different sizes from the input images.
1 code implementation • 24 Mar 2017 • Adnan Qayyum, Syed Muhammad Anwar, Muhammad Awais, Muhammad Majid
The learned features and the classification results are used to retrieve medical images.