Search Results for author: Daniel J. Mollura

Found 9 papers, 0 papers with code

White matter hyperintensity segmentation from T1 and FLAIR images using fully convolutional neural networks enhanced with residual connections

no code implementations19 Mar 2018 Dakai Jin, Ziyue Xu, Adam P. Harrison, Daniel J. Mollura

Segmentation and quantification of white matter hyperintensities (WMHs) are of great importance in studying and understanding various neurological and geriatric disorders.

Progressive and Multi-Path Holistically Nested Neural Networks for Pathological Lung Segmentation from CT Images

no code implementations12 Jun 2017 Adam P. Harrison, Ziyue Xu, Kevin George, Le Lu, Ronald M. Summers, Daniel J. Mollura

Pathological lung segmentation (PLS) is an important, yet challenging, medical image application due to the wide variability of pathological lung appearance and shape.

Holistic Interstitial Lung Disease Detection using Deep Convolutional Neural Networks: Multi-label Learning and Unordered Pooling

no code implementations19 Jan 2017 Mingchen Gao, Ziyue Xu, Le Lu, Adam P. Harrison, Ronald M. Summers, Daniel J. Mollura

Accurately predicting and detecting interstitial lung disease (ILD) patterns given any computed tomography (CT) slice without any pre-processing prerequisites, such as manually delineated regions of interest (ROIs), is a clinically desirable, yet challenging goal.

Computed Tomography (CT) Multi-Label Learning +1

CIDI-Lung-Seg: A Single-Click Annotation Tool for Automatic Delineation of Lungs from CT Scans

no code implementations11 Jul 2014 Awais Mansoor, Ulas Bagci, Brent Foster, Ziyue Xu, Deborah Douglas, Jeffrey M. Solomon, Jayaram K. Udupa, Daniel J. Mollura

Accurate and fast extraction of lung volumes from computed tomography (CT) scans remains in a great demand in the clinical environment because the available methods fail to provide a generic solution due to wide anatomical variations of lungs and existence of pathologies.

Computed Tomography (CT) Semantic Segmentation

Optimally Stabilized PET Image Denoising Using Trilateral Filtering

no code implementations11 Jul 2014 Awais Mansoor, Ulas Bagci, Daniel J. Mollura

Low-resolution and signal-dependent noise distribution in positron emission tomography (PET) images makes denoising process an inevitable step prior to qualitative and quantitative image analysis tasks.

Image Denoising

Near-optimal Keypoint Sampling for Fast Pathological Lung Segmentation

no code implementations11 Jul 2014 Awais Mansoor, Ulas Bagci, Daniel J. Mollura

In this paper, we present a novel approach for fast, accurate, reliable segmentation of pathological lungs from CT scans by combining region-based segmentation method with local descriptor classification that is performed on an optimized sampling grid.

Computed Tomography (CT) General Classification +1

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