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20122023
most citedEvaluating Word Embedding Models: Methods and Experimental Results

331 citations · 576 across the 51 of their papers we have counts for

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10 papers · 1 filter

eess.IV20232 cited

A Comprehensive Overview of Computational Nuclei Segmentation Methods in Digital Pathology

Vasileios Magoulianitis, Catherine A. Alexander, C. -C. Jay Kuo

In the cancer diagnosis pipeline, digital pathology plays an instrumental role in the identification, staging, and grading of malignant areas on biopsy tissue specimens. High resol…

eess.IV2022

LGSQE: Lightweight Generated Sample Quality Evaluatoin

Ganning Zhao, Vasileios Magoulianitis, Suya You +1

Despite prolific work on evaluating generative models, little research has been done on the quality evaluation of an individual generated sample. To address this problem, a lightwe…

eess.IV2022

HUNIS: High-Performance Unsupervised Nuclei Instance Segmentation

Vasileios Magoulianitis, Yijing Yang, C. -C. Jay Kuo

A high-performance unsupervised nuclei instance segmentation (HUNIS) method is proposed in this work. HUNIS consists of two-stage block-wise operations. The first stage includes: 1…

eess.IV20211 cited

Segmentation of Cardiac Structures via Successive Subspace Learning with Saab Transform from Cine MRI

Xiaofeng Liu, Fangxu Xing, Hanna K. Gaggin +4

Assessment of cardiovascular disease (CVD) with cine magnetic resonance imaging (MRI) has been used to non-invasively evaluate detailed cardiac structure and function. Accurate seg…

eess.IV20217 cited

Symmetric-Constrained Irregular Structure Inpainting for Brain MRI Registration with Tumor Pathology

Xiaofeng Liu, Fangxu Xing, Chao Yang +3

Deformable registration of magnetic resonance images between patients with brain tumors and healthy subjects has been an important tool to specify tumor geometry through location a…

eess.IV20219 cited

VoxelHop: Successive Subspace Learning for ALS Disease Classification Using Structural MRI

Xiaofeng Liu, Fangxu Xing, Chao Yang +5

Deep learning has great potential for accurate detection and classification of diseases with medical imaging data, but the performance is often limited by the number of training da…