Iterative probabilistic voxel labeling: automated segmentation for analysis of The Cancer Imaging Archive glioblastoma images
TC Steed, JM Treiber, KS Patel… - American journal …, 2015 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Robust, automated segmentation algorithms are required
for quantitative analysis of large imaging datasets. We developed an automated method that …
for quantitative analysis of large imaging datasets. We developed an automated method that …
Reliability of semi-automated segmentations in glioblastoma
T Huber, G Alber, S Bette, T Boeckh-Behrens… - Clinical …, 2017 - Springer
Purpose In glioblastoma, quantitative volumetric measurements of contrast-enhancing or
fluid-attenuated inversion recovery (FLAIR) hyperintense tumor compartments are needed …
fluid-attenuated inversion recovery (FLAIR) hyperintense tumor compartments are needed …
Tracking tumor growth rates in patients with malignant gliomas: A test of two algorithms
SM Haney, PM Thompson… - American Journal …, 2001 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Two 3D image analysis algorithms, nearest-neighbor
tissue segmentation and surface modeling, were applied separately to serial MR images in …
tissue segmentation and surface modeling, were applied separately to serial MR images in …
Confidence-based ensemble for GBM brain tumor segmentation
It is a challenging task to automatically segment glioblastoma multiforme (GBM) brain tumors
on T1w post-contrast isotropic MR images. A semi-automated system using fuzzy …
on T1w post-contrast isotropic MR images. A semi-automated system using fuzzy …
Automated tumor volumetry using computer-aided image segmentation
Rationale and Objectives Accurate segmentation of brain tumors, and quantification of tumor
volume, is important for diagnosis, monitoring, and planning therapeutic intervention …
volume, is important for diagnosis, monitoring, and planning therapeutic intervention …
Machine learning based brain tumour segmentation on limited data using local texture and abnormality
S Bonte, I Goethals, R Van Holen - Computers in biology and medicine, 2018 - Elsevier
Brain tumour segmentation in medical images is a very challenging task due to the large
variety in tumour shape, position, appearance, scanning modalities and scanning …
variety in tumour shape, position, appearance, scanning modalities and scanning …
Quantitative tumor segmentation for evaluation of extent of glioblastoma resection to facilitate multisite clinical trials
JS Cordova, E Schreibmann, CG Hadjipanayis… - Translational …, 2014 - Elsevier
Standard-of-care therapy for glioblastomas, the most common and aggressive primary adult
brain neoplasm, is maximal safe resection, followed by radiation and chemotherapy …
brain neoplasm, is maximal safe resection, followed by radiation and chemotherapy …
[PDF][PDF] Automatic segmentation of low-grade brain tumor using a random forest classifier and Gabor features
Computerized tumor detection and segmentation algorithms are developed to assist the
work medical staff at the diagnosis or therapy planning. This paper presents a procedure …
work medical staff at the diagnosis or therapy planning. This paper presents a procedure …
[HTML][HTML] Glioblastoma surgery imaging—reporting and data system: Standardized reporting of tumor volume, location, and resectability based on automated …
I Kommers, D Bouget, A Pedersen, RS Eijgelaar… - Cancers, 2021 - mdpi.com
Simple Summary Neurosurgical decisions for patients with glioblastoma depend on tumor
characteristics in the preoperative MR scan. Currently, this is based on subjective estimates …
characteristics in the preoperative MR scan. Currently, this is based on subjective estimates …
Three validation metrics for automated probabilistic image segmentation of brain tumours
KH Zou, WM Wells III, R Kikinis… - Statistics in …, 2004 - Wiley Online Library
The validity of brain tumour segmentation is an important issue in image processing
because it has a direct impact on surgical planning. We examined the segmentation …
because it has a direct impact on surgical planning. We examined the segmentation …