Publications (53)
Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance Imaging
Daniel Capellán-MartÃn, Zhifan Jiang, Abhijeet Parida +8
Segmenting brain tumors in multi-parametric magnetic resonance imaging enables performing quantitative analysis in support of clinical trials and personalized patient care. This an…
Segmentation of Glioma Tumors in Brain Using Deep Convolutional Neural Network
Saddam Hussain, Syed Muhammad Anwar, Muhammad Majid
Detection of brain tumor using a segmentation based approach is critical in cases, where survival of a subject depends on an accurate and timely clinical diagnosis. Gliomas are the…
Foundation Models in Biomedical Imaging: Turning Hype into Reality
Amgad Muneer, Kai Zhang, Ibraheem Hamdi +6
Foundation models (FMs) are driving a prominent shift in biomedical imaging from task-specific models to unified backbone models for diverse tasks. This opens an avenue to integrat…
MedLeak: Multimodal Medical Data Leakage in Secure Federated Learning with Crafted Models
Shanghao Shi, Md Shahedul Haque, Abhijeet Parida +5
Federated learning (FL) allows participants to collaboratively train machine learning models while keeping their data local, making it ideal for collaborations among healthcare ins…
A Survey on Recent Advancements for AI Enabled Radiomics in Neuro-Oncology
Syed Muhammad Anwar, Tooba Altaf, Khola Rafique +3
Artificial intelligence (AI) enabled radiomics has evolved immensely especially in the field of oncology. Radiomics provide assistancein diagnosis of cancer, planning of treatment…
Analysis of the MICCAI Brain Tumor Segmentation -- Metastases (BraTS-METS) 2025 Lighthouse Challenge: Brain Metastasis Segmentation on Pre- and Post-treatment MRI
Nazanin Maleki, Raisa Amiruddin, Ahmed W. Moawad +240
Despite continuous advancements in cancer treatment, brain metastatic disease remains a significant complication of primary cancer and is associated with an unfavorable prognosis.…
Deep Learning for Musculoskeletal Image Analysis
Ismail Irmakci, Syed Muhammad Anwar, Drew A. Torigian +1
The diagnosis, prognosis, and treatment of patients with musculoskeletal (MSK) disorders require radiology imaging (using computed tomography, magnetic resonance imaging(MRI), and…
Improving Pre-trained Adult Glioma Segmentation Models Using only Post-processing Techniques
Abhijeet Parida, Daniel Capellán-MartÃn, Zhifan Jiang +6
Gliomas are the most common malignant brain tumors in adults and are among the most lethal. Despite aggressive treatment, the median survival rate is less than 15 months. Accurate…
Variational Capsule Encoder
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 distributi…
SelfFed: Self-Supervised Federated Learning for Data Heterogeneity and Label Scarcity in Medical Images
Sunder Ali Khowaja, Kapal Dev, Syed Muhammad Anwar +1
Self-supervised learning in the federated learning paradigm has been gaining a lot of interest both in industry and research due to the collaborative learning capability on unlabel…
Semi-Supervised Deep Learning for Multi-Tissue Segmentation from Multi-Contrast MRI
Syed Muhammad Anwar, Ismail Irmakci, Drew A. Torigian +5
Segmentation of thigh tissues (muscle, fat, inter-muscular adipose tissue (IMAT), bone, and bone marrow) from magnetic resonance imaging (MRI) scans is useful for clinical and rese…
Harmonization Across Imaging Locations(HAIL): One-Shot Learning for Brain MRI
Abhijeet Parida, Zhifan Jiang, Syed Muhammad Anwar +6
For machine learning-based prognosis and diagnosis of rare diseases, such as pediatric brain tumors, it is necessary to gather medical imaging data from multiple clinical sites tha…
EMeRALDS: Electronic Medical Record Driven Automated Lung Nodule Detection and Classification in Thoracic CT Images
Hafza Eman, Furqan Shaukat, Muhammad Hamza Zafar +1
Objective: Lung cancer is a leading cause of cancer-related mortality worldwide, primarily due to delayed diagnosis and poor early detection. This study aims to develop a computer-…
Lung-CADex: Fully automatic Zero-Shot Detection and Classification of Lung Nodules in Thoracic CT Images
Furqan Shaukat, Syed Muhammad Anwar, Abhijeet Parida +3
Lung cancer has been one of the major threats to human life for decades. Computer-aided diagnosis can help with early lung nodul detection and facilitate subsequent nodule characte…
Deep Convolutional Neural Network based Classification of Alzheimer's Disease using MRI data
Ali Nawaz, Syed Muhammad Anwar, Rehan Liaqat +3
Alzheimer's disease (AD) is a progressive and incurable neurodegenerative disease which destroys brain cells and causes loss to patient's memory. An early detection can prevent the…
MRI-to-CT Synthesis With Cranial Suture Segmentations Using A Variational Autoencoder Framework
Krithika Iyer, Austin Tapp, Athelia Paulli +4
Quantifying normative pediatric cranial development and suture ossification is crucial for diagnosing and treating growth-related cephalic disorders. Computed tomography (CT) is wi…
Adaptable Segmentation Pipeline for Diverse Brain Tumors with Radiomic-Guided Subtyping and Lesion-Wise Model Ensemble
Daniel Capellán-MartÃn, Abhijeet Parida, Zhifan Jiang +6
Robust and generalizable segmentation of brain tumors on multi-parametric magnetic resonance imaging (MRI) remains difficult because tumor types differ widely. The BraTS 2025 Light…
LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis
Zhifan Jiang, Dong Yang, Vishwesh Nath +7
Large vision-language models (VLMs) have evolved from general-purpose applications to specialized use cases such as in the clinical domain, demonstrating potential for decision sup…
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn)
Hongwei Bran Li, Gian Marco Conte, Qingqiao Hu +62
Automated brain tumor segmentation methods have become well-established and reached performance levels offering clear clinical utility. These methods typically rely on four input m…
SB-SSL: Slice-Based Self-Supervised Transformers for Knee Abnormality Classification from MRI
Sara Atito, Syed Muhammad Anwar, Muhammad Awais +1
The availability of large scale data with high quality ground truth labels is a challenge when developing supervised machine learning solutions for healthcare domain. Although, the…
Human Stress Assessment: A Comprehensive Review of Methods Using Wearable Sensors and Non-wearable Techniques
Aamir Arsalan, Muhammad Majid, Imran Fareed Nizami +3
This paper presents a comprehensive review of methods covering significant subjective and objective human stress detection techniques available in the literature. The methods for m…
Dual-Task Graph Neural Network for Joint Seizure Onset Zone Localization and Outcome Prediction using Stereo EEG
Syeda Abeera Amir, Artur Agaronyan, William Gaillard +2
Accurately localizing the brain regions that triggers seizures and predicting whether a patient will be seizure-free after surgery are vital for surgical planning and patient manag…
A Multi-Dimensional Clustering Approach for Identifying Inborn Errors of Immunity
Nishad Kulkarni, Alexandra K. Martinson, Nicholas L. Rider +2
Rare diseases such as inborn errors of immunity (IEI) require early diagnosis to prevent end organ damage and improve quality of life. Hurdles in accessing and curating large scale…
Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Data
Abhijeet Parida, Daniel Capellán-MartÃn, Zhifan Jiang +5
Gliomas, a kind of brain tumor characterized by high mortality, present substantial diagnostic challenges in low- and middle-income countries, particularly in Sub-Saharan Africa. T…
M-Net with Bidirectional ConvLSTM for Cup and Disc Segmentation in Fundus Images
Maleeha Khalid Khan, Syed Muhammad Anwar
Glaucoma is a severe eye disease that is known to deteriorate optic never fibers, causing cup size to increase, which could result in permanent loss of vision. Glaucoma is the seco…
Human Emotions Analysis and Recognition Using EEG Signals in Response to 360 Videos
Haseeb ur Rahman Abbasi, Zeeshan Rashid, Muhammad Majid +1
Emotion recognition (ER) technology is an integral part for developing innovative applications such as drowsiness detection and health monitoring that plays a pivotal role in conte…
The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting
Florian Kofler, Felix Meissen, Felix Steinbauer +103
A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition ti…
Medical Image Retrieval using Deep Convolutional Neural Network
Adnan Qayyum, Syed Muhammad Anwar, Muhammad Awais +1
With a widespread use of digital imaging data in hospitals, the size of medical image repositories is increasing rapidly. This causes difficulty in managing and querying these larg…
Brain Tumor Survival Prediction using Radiomics Features
Sobia Yousaf, Syed Muhammad Anwar, Harish RaviPrakash +1
Surgery planning in patients diagnosed with brain tumor is dependent on their survival prognosis. A poor prognosis might demand for a more aggressive treatment and therapy plan, wh…
FeTTL: Federated Template and Task Learning for Multi-Institutional Medical Imaging
Abhijeet Parida, Antonia Alomar, Zhifan Jiang +7
Federated learning enables collaborative model training across geographically distributed medical centers while preserving data privacy. However, domain shifts and heterogeneity in…
Post-Processing Methods for Improving Accuracy in MRI Inpainting
Nishad Kulkarni, Krithika Iyer, Austin Tapp +6
Magnetic Resonance Imaging (MRI) is the primary imaging modality used in the diagnosis, assessment, and treatment planning for brain pathologies. However, most automated MRI analys…
Self-supervised Graph Transformer with Contrastive Learning for Brain Connectivity Analysis towards Improving Autism Detection
Yicheng Leng, Syed Muhammad Anwar, Islem Rekik +2
Functional Magnetic Resonance Imaging (fMRI) provides useful insights into the brain function both during task or rest. Representing fMRI data using correlation matrices is found t…
Electroencephalography based Classification of Long-term Stress using Psychological Labeling
Sanay Muhammad Umar Saeed, Syed Muhammad Anwar, Humaira Khalid +2
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 andpersonal…
Medical Image Analysis using Convolutional Neural Networks: A Review
Syed Muhammad Anwar, Muhammad Majid, Adnan Qayyum +3
The science of solving clinical problems by analyzing images generated in clinical practice is known as medical image analysis. The aim is to extract information in an effective an…
Graph-Based Deep Learning on Stereo EEG for Predicting Seizure Freedom in Epilepsy Patients
Artur Agaronyan, Syeda Abeera Amir, Nunthasiri Wittayanakorn +5
Predicting seizure freedom is essential for tailoring epilepsy treatment. But accurate prediction remains challenging with traditional methods, especially with diverse patient popu…
VolTA-3D: Self-Supervised Learning for Brain MRI using 3D Volumetric Token Alignment
Amy Makawana, Abhijeet Parida, Marius George Linguraru +2
Self-supervised learning (SSL) has advanced medical image analysis be enabling learning form large unlabelled data. However, in brain magnetic resonance imaging (MRI), most 3D mode…
Personality Trait Recognition using ECG Spectrograms and Deep Learning
Muhammad Mohsin Altaf, Saadat Ullah Khan, Muhammad Majd +1
This paper presents an innovative approach to recognizing personality traits using deep learning (DL) methods applied to electrocardiogram (ECG) signals. Within the framework of de…
DiCoM -- Diverse Concept Modeling towards Enhancing Generalizability in Chest X-Ray Studies
Abhijeet Parida, Daniel Capellan-Martin, Sara Atito +4
Chest X-Ray (CXR) is a widely used clinical imaging modality and has a pivotal role in the diagnosis and prognosis of various lung and heart related conditions. Conventional automa…
Upper Limb Movement Execution Classification using Electroencephalography for Brain Computer Interface
Saadat Ullah Khan, Muhammad Majid, Syed Muhammad Anwar
An accurate classification of upper limb movements using electroencephalography (EEG) signals is gaining significant importance in recent years due to the prevalence of brain-compu…
Analysis of the 2024 BraTS Meningioma Radiotherapy Planning Automated Segmentation Challenge
Dominic LaBella, Valeriia Abramova, Mehdi Astaraki +102
The 2024 Brain Tumor Segmentation Meningioma Radiotherapy (BraTS-MEN-RT) challenge aimed to advance automated segmentation algorithms using the largest known multi-institutional da…
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
Dominic LaBella, Ujjwal Baid, Omaditya Khanna +119
We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in…
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Ahmed W. Moawad, Anastasia Janas, Ujjwal Baid +229
The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS…
Emotion Classification in Response to Tactile Enhanced Multimedia using Frequency Domain Features of Brain Signals
Aasim Raheel, Muhammad Majid, Syed Muhammad Anwar +1
Tactile enhanced multimedia is generated by synchronizing traditional multimedia clips, to generate hot and cold air effect, with an electric heater and a fan. This objective is to…
SPCXR: Self-supervised Pretraining using Chest X-rays Towards a Domain Specific Foundation Model
Syed Muhammad Anwar, Abhijeet Parida, Sara Atito +4
Chest X-rays (CXRs) are a widely used imaging modality for the diagnosis and prognosis of lung disease. The image analysis tasks vary. Examples include pathology detection and lung…
Development of a Modular Real-time Shared-control System for a Smart Wheelchair
Vaishanth Ramaraj, Atharva Paralikar, Eung Joo Lee +2
In this paper, we propose a modular navigation system that can be mounted on a regular powered wheelchair to assist disabled children and the elderly with autonomous mobility and s…
D-Rax: Domain-specific Radiologic assistant leveraging multi-modal data and eXpert model predictions
Hareem Nisar, Syed Muhammad Anwar, Zhifan Jiang +5
Large vision language models (VLMs) have progressed incredibly from research to applicability for general-purpose use cases. LLaVA-Med, a pioneering large language and vision assis…
Motor imagery classification using EEG spectrograms
Saadat Ullah Khan, Muhammad Majid, Syed Muhammad Anwar
The loss of limb motion arising from damage to the spinal cord is a disability that could effect people while performing their day-to-day activities. The restoration of limb moveme…
An ADHD Diagnostic Interface Based on EEG Spectrograms and Deep Learning Techniques
Medha Pappula, Syed Muhammad Anwar
This paper introduces an innovative approach to Attention-deficit/hyperactivity disorder (ADHD) diagnosis by employing deep learning (DL) techniques on electroencephalography (EEG)…
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma
Dominic LaBella, Maruf Adewole, Michelle Alonso-Basanta +57
Meningiomas are the most common primary intracranial tumor in adults and can be associated with significant morbidity and mortality. Radiologists, neurosurgeons, neuro-oncologists,…
Classification of Perceived Human Stress using Physiological Signals
Aamir Arsalan, Muhammad Majid, Syed Muhammad Anwar +1
In this paper, we present an experimental study for the classification of perceived human stress using non-invasive physiological signals. These include electroencephalography (EEG…
Geometric Deep Learning for Automated Landmarking of Maxillary Arches on 3D Oral Scans from Newborns with Cleft Lip and Palate
Artur Agaronyan, HyeRan Choo, Marius Linguraru +1
Rapid advances in 3D model scanning have enabled the mass digitization of dental clay models. However, most clinicians and researchers continue to use manual morphometric analysis…
Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation
Zhifan Jiang, Daniel Capellán-MartÃn, Abhijeet Parida +5
Accurate and automatic segmentation of brain tumors in multi-parametric magnetic resonance imaging (mpMRI) is essential for quantitative measurements, which play an increasingly im…
A Multimodal Perceived Stress Classification Framework using Wearable Physiological Sensors
Muhammad Majid, Aamir Arsalan, Syed Muhammad Anwar
Mental stress is a largely prevalent condition known to affect many people and could be a serious health concern. The quality of human life can be significantly improved if mental…