activity
20222024
most citedThe ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma

27 citations · 31 across the 11 of their papers we have counts for

collaborators

11 papers

eess.IV20241 cited

Adult Glioma Segmentation in Sub-Saharan Africa using Transfer Learning on Stratified Finetuning Data

Abhijeet Parida, Daniel Capellán-Martín, 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…

eess.IV20241 cited

Magnetic Resonance Imaging Feature-Based Subtyping and Model Ensemble for Enhanced Brain Tumor Segmentation

Zhifan Jiang, Daniel Capellán-Martín, 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…

cs.CY20241 cited

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)…

cs.AI2024

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…

eess.IV2024

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…

cs.HC2024

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…