Ultrasonic Tissue Characterization with Gray Level Histogram Width

Author(s):  
Kazuo Maeda ◽  
Masaji Utsu ◽  
Nobuhiro Yamamoto ◽  
Mariko Serizawa
2001 ◽  
Vol 18 ◽  
pp. F27-F27
Author(s):  
K. Maeda ◽  
M. Utsu ◽  
P. E. Kihaile ◽  
M. Serizawa ◽  
N. Yamamoto ◽  
...  

Author(s):  
Kazuo Maeda ◽  
PE Kihaile ◽  
T Ito ◽  
M Utsu ◽  
N Yamamoto ◽  
...  

ABSTRACT Aim Clinical ultrasound tissue characterization, using usual B-mode devices. Materials and methods Malignant neoplasia in ovary, uterine cervix, and endometrium; placental intervillous space fibrin deposit; fetal growth restriction; fetal brain, fetal lung immaturity; meconium-stained amniotic fluid and healthy adult liver; Tissue was characterized by gray-level histogram width (GLHW) divided by full gray scale length. Results Malignant GLHW was higher than in benign one (it was malignant if the GLHW was 50% or more in ovary, uterine cervix, and endometrium). The GLHW of placental fibrin deposit was higher than normal placenta. It was reduced by heparin and normal neonate was obtained. Fetal brain echo density, immature fetal lung, and meconium-stained amniotic fluid were diagnosed by GLHW, and normal adult liver GLHW was studied. Helsinki declaration was followed. Conclusion The GLHW tissue characterization objectively diagnosed ultrasound B-mode image in obstetrics and gynecology; thus, it would also be applied in common adult human cases. How to cite this article Maeda K, Kihaile PE, Ito T, Utsu M, Yamamoto N, Serizawa M. Tissue Characterization with Gray-level Histogram Width in Obstetrics and Gynecology. Donald School J Ultrasound Obstet Gynecol 2017;11(1):7-10.


2007 ◽  
Vol 34 (4) ◽  
pp. 189-192 ◽  
Author(s):  
Takashi ITO ◽  
Koichi ISHIHARA ◽  
Imari DEURA ◽  
Chieko KATAGIRI ◽  
Kazuo MAEDA

Author(s):  
Kazuo Maeda ◽  
Masaji Utsu ◽  
Nobuhiro Yamamoto ◽  
Mariko Serizawa

1996 ◽  
Vol 18 (4) ◽  
pp. 261-304 ◽  
Author(s):  
Y. V. Venkatesh

Ultrasonic images of the kidney and of the liver are subjected to a multiscale analysis in a generalized Hermite pyramid framework. The gradient images of the multiscale decompositions of the images of healthy and sick kidneys, and of the intraoperative and conventionally imaged livers, exhibit differences, in the structures of gray level regions, which can be interpreted by a medical doctor. These are used as inputs to an unsupervised classifier to automatically classify the images into homogeneous groups, which are found, in the case of the ultrasonic images examined, to correspond to the different physical characteristics of tissues of the organs under study. The main contribution of the paper is believed to be the multiscale tissue characterization along with its display in a manner that has utility as a diagnostic aid to the clinician.


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