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20232025
most citedA Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection

14 citations · 42 across the 10 of their papers we have counts for

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eess.IV2024★ 1 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.IV2024★ 1 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…

eess.IV2024★ 12 cited

Model Ensemble for Brain Tumor Segmentation in Magnetic Resonance Imaging

Daniel Capellán-Martín, 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…

eess.IV2024

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…

eess.IV2023★ 14 cited

A Lightweight, Rapid and Efficient Deep Convolutional Network for Chest X-Ray Tuberculosis Detection

Daniel Capellán-Martín, Juan J. Gómez-Valverde, David Bermejo-Peláez +1

Tuberculosis (TB) is still recognized as one of the leading causes of death worldwide. Recent advances in deep learning (DL) have shown to enhance radiologists' ability to interpre…