most citedAutomated Segmentation of CT Scans for Normal Pressure Hydrocephalus

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

collaborators

5 papers

eess.IV2019

Predicting Clinical Outcome of Stroke Patients with Tractographic Feature

Po-Yu Kao, Jefferson W. Chen, B. S. Manjunath

The volume of stroke lesion is the gold standard for predicting the clinical outcome of stroke patients. However, the presence of stroke lesion may cause neural disruptions to othe…

cs.CV2019

Improving 3D U-Net for Brain Tumor Segmentation by Utilizing Lesion Prior

Po-Yu Kao, Jefferson W. Chen, B. S. Manjunath

We propose a novel, simple and effective method to integrate lesion prior and a 3D U-Net for improving brain tumor segmentation. First, we utilize the ground-truth brain tumor lesi…

cs.LG2019

Predicting Fluid Intelligence of Children using T1-weighted MR Images and a StackNet

Po-Yu Kao, Angela Zhang, Michael Goebel +2

In this work, we utilize T1-weighted MR images and StackNet to predict fluid intelligence in adolescents. Our framework includes feature extraction, feature normalization, feature…

eess.IV20191 cited

Automated Segmentation of CT Scans for Normal Pressure Hydrocephalus

Angela Zhang, Po-Yu Kao, Ronald Sahyouni +3

Normal Pressure Hydrocephalus (NPH) is one of the few reversible forms of dementia, Due to their low cost and versatility, Computed Tomography (CT) scans have long been used as an…

cs.CV2018

Brain Tumor Segmentation and Tractographic Feature Extraction from Structural MR Images for Overall Survival Prediction

Po-Yu Kao, Thuyen Ngo, Angela Zhang +2

This paper introduces a novel methodology to integrate human brain connectomics and parcellation for brain tumor segmentation and survival prediction. For segmentation, we utilize…