scholarly journals Diminishing the impact of the partial volume effect in cardiac SPECT perfusion imaging

2008 ◽  
Vol 36 (1) ◽  
pp. 105-115 ◽  
Author(s):  
P. Hendrik Pretorius ◽  
Michael A. King
Keyword(s):  
Perfusion Imaging ◽  
Volume Effect ◽  
Partial Volume Effect ◽  
Cardiac Spect ◽  
Partial Volume ◽  
The Impact

scholarly journals Impact of Different Analytic Approaches on the Analysis of the Breast Fibroglandular Tissue Using Diffusion Weighted Imaging

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yoon Jung Choi ◽  
Jeon-Hor Chen ◽  
Hon J. Yu ◽  
Yifan Li ◽  
Min-Ying Su
Keyword(s):  
Region Of Interest ◽  
Volume Effect ◽  
Partial Volume Effect ◽  
Normal Breast ◽  
Unilateral Breast Cancer ◽  
Partial Volume ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Highly Correlated ◽  
The Impact

Purpose. This study investigated the impact of the different region of interest (ROI) approaches on measurement of apparent diffusion coefficient (ADC) values in the breast firbroglandular tissue (FT). Methods. Breast MR images of 38 women diagnosed with unilateral breast cancer were studied. Percent density (PD) and ADC were measured from the contralateral normal breast. Four different ROIs were used for ADC measurement. The measured PD and ADC were correlated. Results. Among the four ROIs, the manually placed small ROI on FT gave the highest mean ADC (ADC = 1839 ± 343 [×10−6 mm2/s]), while measurement from the whole breast gave the lowest mean ADC (ADC = 933 ± 383 [×10−6 mm2/s]). The ADC measured from the whole breast was highly correlated with PD with r=0.95. In slice-to-slice comparison, the central slices with more FT had higher ADC values than the peripheral slices did, presumably due to less partial volume effect from fat. Conclusions. Our results indicated that the measured ADC heavily depends on the composition of breast tissue contained in the ROI used for the ADC measurements. Women with low breast density showing lower ADC values were most likely due to the partial volume effect of fatty tissues.

Partial volume effect of SPECT images in PRRT with 177Lu labelled somatostatin analogues: A practical solution

2019 ◽  
Vol 57 ◽  
pp. 153-159 ◽  
Author(s):  
Domenico Finocchiaro ◽  
Salvatore Berenato ◽  
Elisa Grassi ◽  
Valentina Bertolini ◽  
Gastone Castellani ◽  
...  
Keyword(s):  
Somatostatin Analogues ◽  
Volume Effect ◽  
Partial Volume Effect ◽  
Practical Solution ◽  
Partial Volume ◽  
Spect Images

Spectrum separation resolves partial-volume effect of MRSI as demonstrated on brain tumor scans

2008 ◽  
Vol 21 (10) ◽  
pp. 1030-1042 ◽  
Author(s):  
Yuzhuo Su ◽  
Sunitha B. Thakur ◽  
Karimi Sasan ◽  
Shuyan Du ◽  
Paul Sajda ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Volume Effect ◽  
Partial Volume Effect ◽  
Partial Volume

Segmentation of the skull in MRI volumes using a deformable model and taking the partial volume effect into account

1999 ◽  
Author(s):  
Hilmi Rifai ◽  
Isabelle Bloch ◽  
Seth A. Hutchinson ◽  
Joe Wiart ◽  
Line Garnero
Keyword(s):  
Volume Effect ◽  
Partial Volume Effect ◽  
Deformable Model ◽  
Partial Volume

scholarly journals Ventricle Boundary in CT: Partial Volume Effect and Local Thresholds

2010 ◽  
Vol 2010 ◽  
pp. 1-6 ◽  
Author(s):  
Ihar Volkau ◽  
Fiftarina Puspitasari ◽  
Wieslaw L. Nowinski
Keyword(s):  
Computed Tomography ◽  
Cerebrospinal Fluid ◽  
Grey Matter ◽  
Ground Truth ◽  
Gaussian Mixture ◽  
Volume Effect ◽  
Partial Volume Effect ◽  
Partial Volume ◽  
Image Histogram ◽  
Global Threshold

We present a mathematical frame to carry out segmentation of cerebrospinal fluid (CSF) of ventricular region in computed tomography (CT) images in the presence of partial volume effect (PVE). First, the image histogram is fitted using the Gaussian mixture model (GMM). Analyzing the GMM, we find global threshold based on parameters of distributions for CSF, and for the combined white and grey matter (WGM). The parameters of distribution of PVE pixels on the boundary of ventricles are estimated by using a convolution operator. These parameters are used to calculate local thresholds for boundary pixels by the analysis of contribution of the neighbor pixels intensities into a PVE pixel. The method works even in the case of an almost unimodal histogram; it can be useful to analyze the parameters of PVE in the ground truth provided by the expert.

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