most citedImproving Pre-trained Adult Glioma Segmentation Models Using only Post-processing Techniques

1 citations · 1 across the 2 of their papers we have counts for

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5 papers

cs.CV20261 cited

Improving Pre-trained Adult Glioma Segmentation Models Using only Post-processing Techniques

Abhijeet Parida, Daniel Capellán-Martín, 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…

cs.CV2026

Adaptable Segmentation Pipeline for Diverse Brain Tumors with Radiomic-Guided Subtyping and Lesion-Wise Model Ensemble

Daniel Capellán-Martín, 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…

cs.CV2026

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…

eess.IV2024

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

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…