scholarly journals Cardiac-gated parametric images from 82 Rb PET from dynamic frames and direct 4D reconstruction

2017 ◽  
Vol 45 (2) ◽  
pp. 639-654 ◽  
Author(s):  
Mary Germino ◽  
Richard E. Carson
Keyword(s):  
Parametric Images ◽  
4D Reconstruction

scholarly journals Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy

2010 ◽  
Vol 55 (15) ◽  
pp. 4261-4272 ◽  
Author(s):  
Jing Tang ◽  
Hiroto Kuwabara ◽  
Dean F Wong ◽  
Arman Rahmim
Keyword(s):  
Joint Entropy ◽  
Parametric Images ◽  
4D Reconstruction

Direct 4D reconstruction of parametric images incorporating anato-functional joint entropy

2008 ◽  
Author(s):  
Jing Tang ◽  
Hiroto Kuwabara ◽  
Dean F. Wong ◽  
Arman Rahmim
Keyword(s):  
Joint Entropy ◽  
Parametric Images ◽  
4D Reconstruction

Basic Ideas and Principles for Quantifying Regional Blood Flow with Nuclear Medical Techniques

1996 ◽  
Vol 35 (05) ◽  
pp. 181-185 ◽  
Author(s):  
H. Herzog
Keyword(s):  
Blood Flow ◽  
Nuclear Medicine ◽  
Regional Blood Flow ◽  
Visual Presentation ◽  
Regional Cerebral Blood ◽  
Basic Principles ◽  
Parametric Images ◽  
Major Application ◽  
Basic Ideas ◽  
The Brain

SummaryThe measurement of blood flow in various organs and its visual presentation in parametric images is a major application in nuclear medicine. The purpose of this paper is to summarize the most important nuclear medicine procedures used to quantify regional blood flow. Starting with the first concepts introduced by Fick and later by Kety-Schmidt the basic principles of measuring global and regional cerebral blood are discussed and their relationships are explained. Different applications and modifications realized first in PET- and later in SPECT-studies of the brain and other organs are described. The permeability and the extraction of the different radiopharmaceuticals are considered. Finally some important instrumental implications are compared.

scholarly journals Characterizing intra-tumor regions on quantitative ultrasound parametric images to predict breast cancer response to chemotherapy at pre-treatment

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hamidreza Taleghamar ◽  
Hadi Moghadas-Dastjerdi ◽  
Gregory J. Czarnota ◽  
Ali Sadeghi-Naini
Keyword(s):  
Breast Cancer ◽  
Treatment Response ◽  
Quantitative Ultrasound ◽  
Parametric Imaging ◽  
Term Survival ◽  
Adaptive Boosting ◽  
Tumor Margin ◽  
Parametric Images ◽  
Response To Chemotherapy ◽  
Pre Treatment

AbstractThe efficacy of quantitative ultrasound (QUS) multi-parametric imaging in conjunction with unsupervised classification algorithms was investigated for the first time in characterizing intra-tumor regions to predict breast tumor response to chemotherapy before the start of treatment. QUS multi-parametric images of breast tumors were generated using the ultrasound radiofrequency data acquired from 181 patients diagnosed with locally advanced breast cancer and planned for neo-adjuvant chemotherapy followed by surgery. A hidden Markov random field (HMRF) expectation maximization (EM) algorithm was applied to identify distinct intra-tumor regions on QUS multi-parametric images. Several features were extracted from the segmented intra-tumor regions and tumor margin on different parametric images. A multi-step feature selection procedure was applied to construct a QUS biomarker consisting of four features for response prediction. Evaluation results on an independent test set indicated that the developed biomarker coupled with a decision tree model with adaptive boosting (AdaBoost) as the classifier could predict the treatment response of patient at pre-treatment with an accuracy of 85.4% and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.89. In comparison, the biomarkers consisted of the features derived from the entire tumor core (without consideration of the intra-tumor regions), and the entire tumor core and the tumor margin could predict the treatment response of patients with an accuracy of 74.5% and 76.4%, and an AUC of 0.79 and 0.76, respectively. Standard clinical features could predict the therapy response with an accuracy of 69.1% and an AUC of 0.6. Long-term survival analyses indicated that the patients predicted by the developed model as responders had a significantly better survival compared to the non-responders. Similar findings were observed for the two response cohorts identified at post-treatment based on standard clinical and pathological criteria. The results obtained in this study demonstrated the potential of QUS multi-parametric imaging integrated with unsupervised learning methods in identifying distinct intra-tumor regions in breast cancer to characterize its responsiveness to chemotherapy prior to the start of treatment.

Breast tumor classification using different features of quantitative ultrasound parametric images

2019 ◽  
Vol 14 (4) ◽  
pp. 623-633 ◽  
Author(s):  
Soa-Min Hsu ◽  
Wen-Hung Kuo ◽  
Fang-Chuan Kuo ◽  
Yin-Yin Liao
Keyword(s):  
Quantitative Ultrasound ◽  
Breast Tumor ◽  
Tumor Classification ◽  
Parametric Images ◽  
Breast Tumor Classification

scholarly journals Joint reconstruction of dynamic PET activity and kinetic parametric images using total variation constrained dictionary sparse coding

2017 ◽  
Vol 33 (5) ◽  
pp. 055011 ◽  
Author(s):  
Haiqing Yu ◽  
Shuhang Chen ◽  
Yunmei Chen ◽  
Huafeng Liu
Keyword(s):  
Total Variation ◽  
Sparse Coding ◽  
Dynamic Pet ◽  
Parametric Images ◽  
Joint Reconstruction

scholarly journals Measurement of Blood—Brain Hexose Transport with Dynamic PET: Comparison of [18F]2-Fluoro-2-Deoxyglucose and [11C]O-Methylglucose

1989 ◽  
Vol 9 (1) ◽  
pp. 104-110 ◽  
Author(s):  
K. Herholz ◽  
K. Wienhard ◽  
U. Pietrzyk ◽  
G. Pawlik ◽  
W.-D. Heiss
Keyword(s):  
Blood Volume ◽  
Rate Constants ◽  
Regional Analysis ◽  
Close Correlation ◽  
Transport Rate ◽  
Hexose Transport ◽  
Tracer Transport ◽  
Parametric Images ◽  
Positron Emission ◽  
Regional Blood Volume

Blood-to-tissue transport of [18F]2-fluoro-2-deoxyglucose (FDG) and [11C]O-methylglucose (CMG) was compared by dynamic positron emission tomography in four patients with recent ischemic infarcts and in three patients with intracerebral tumors. Local blood volume, tracer transport from tissue to blood, and FDG phosphorylation rates were also determined. A regional analysis of parametric images showed a close correlation of FDG and CMG transport rate constants in pathological tissue. Transport rates of FDG and CMG showed correspondingly less asymmetric remote effects than FDG phosphorylation rates. Transport rate constants were consistently higher for FDG than for CMG in pathological and normal tissue, in accordance with the higher affinity of carrier enzymes to FDG. There was a significant correlation between fitted regional blood volume values and correspondence of average absolute values with both tracers. It is concluded that dynamic FDG PET for measurement of cerebral glucose metabolism is also useful to measure alterations of hexose transport and local blood volume in pathological tissue.

Generation of Parametric Images during Routine Tc-99m PYP lnhalationlTc-99m MAA Perfusion Lung Scintigraphy

1991 ◽  
Vol 16 (7) ◽  
pp. 501-505 ◽  
Author(s):  
STEFAN D. MIRON ◽  
ERNEST J. WIESEN ◽  
DAVID H. FEIGLIN ◽  
ALAN M. COHEN ◽  
ERROL M. BELLON
Keyword(s):  
Lung Scintigraphy ◽  
Parametric Images ◽  
Perfusion Lung Scintigraphy

scholarly journals Using the rPatlak plot and dynamic FDG-PET to generate parametric images of relative local cerebral metabolic rate of glucose

2012 ◽  
Vol 57 (28-29) ◽  
pp. 3811-3818 ◽  
Author(s):  
YiGen Wu ◽  
Yun Zhou ◽  
ShangLian Bao ◽  
SungCheng Huang ◽  
XiaoHu Zhao ◽  
...  
Keyword(s):  
Metabolic Rate ◽  
Fdg Pet ◽  
Parametric Images ◽  
Cerebral Metabolic Rate

A New PET Camera for Noninvasive Quantitation of Physiological Functional Parametric Images

1996 ◽  
pp. 57-61 ◽  
Author(s):  
HIDEHIRO IIDA ◽  
SHUICHI MIURA ◽  
IWAO KANNO ◽  
TOSHIHIDE OGAWA ◽  
KAZUO UEMURA
Keyword(s):  
Parametric Images
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