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20192026
most citedTowards Optimal Patch Size in Vision Transformers for Tumor Segmentation

14 citations · 22 across the 8 of their papers we have counts for

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eess.IV20252 cited

Finding Reproducible and Prognostic Radiomic Features in Variable Slice Thickness Contrast Enhanced CT of Colorectal Liver Metastases

Jacob J. Peoples, Mohammad Hamghalam, Imani James +7

Establishing the reproducibility of radiomic signatures is a critical step in the path to clinical adoption of quantitative imaging biomarkers; however, radiomic signatures must al…

eess.IV2021

Modality Completion via Gaussian Process Prior Variational Autoencoders for Multi-Modal Glioma Segmentation

Mohammad Hamghalam, Alejandro F. Frangi, Baiying Lei +1

In large studies involving multi protocol Magnetic Resonance Imaging (MRI), it can occur to miss one or more sub-modalities for a given patient owing to poor quality (e.g. imaging…

eess.IV2020

Convolutional 3D to 2D Patch Conversion for Pixel-wise Glioma Segmentation in MRI Scans

Mohammad Hamghalam, Baiying Lei, Tianfu Wang

Structural magnetic resonance imaging (MRI) has been widely utilized for analysis and diagnosis of brain diseases. Automatic segmentation of brain tumors is a challenging task for…

eess.IV20202 cited

High Tissue Contrast MRI Synthesis Using Multi-Stage Attention-GAN for Glioma Segmentation

Mohammad Hamghalam, Baiying Lei, Tianfu Wang

Magnetic resonance imaging (MRI) provides varying tissue contrast images of internal organs based on a strong magnetic field. Despite the non-invasive advantage of MRI in frequent…

eess.IV2019

Brain Tumor Synthetic Segmentation in 3D Multimodal MRI Scans

Mohammad Hamghalam, Baiying Lei, Tianfu Wang

The magnetic resonance (MR) analysis of brain tumors is widely used for diagnosis and examination of tumor subregions. The overlapping area among the intensity distribution of heal…