Salt distribution in dry-cured ham measured by computed tomography and image analysis

Meat Science ◽  
2005 ◽  
Vol 69 (1) ◽  
pp. 9-15 ◽  
Author(s):  
Christian Vestergaard ◽  
Søren G. Erbou ◽  
Torunn Thauland ◽  
Jens Adler-Nissen ◽  
Per Berg
2021 ◽  
pp. 101969
Author(s):  
Hiroko Indo ◽  
Hiromu Ito ◽  
Chihaya Koriyama ◽  
Hideyuki J. Majima ◽  
Kazuyuki Shimada ◽  
...  

2019 ◽  
Vol 12 (1) ◽  
pp. 31-37
Author(s):  
Dave R Shukla ◽  
Richard J McLaughlin ◽  
Julia Lee ◽  
Ngoc Tram V Nguyen ◽  
Joaquin Sanchez-Sotelo

Background Preoperative planning software has been developed to measure glenoid version, glenoid inclination, and humeral head subluxation on computed tomography (CT) for shoulder arthroplasty. However, most studies analyzing the effect of glenoid positioning on outcome were done prior to the introduction of planning software. Thus, measurements obtained from the software can only be extrapolated to predict failure provided they are similar to classic measurements. The purpose of this study was to compare measurements obtained using classic manual measuring techniques and measurements generated from automated image analysis software. Methods Ninety-five two-dimensional computed tomography scans of shoulders with primary glenohumeral osteoarthritis were measured for version according to Friedman method, inclination according to Maurer method, and subluxation according to Walch method. DICOM files were loaded into an image analysis software (Blueprint, Wright Medical) and the output was compared with values obtained manually using a paired sample t-test. Results Average manual measurements included 13.8° version, 13.2° inclination, and 56.2% subluxation. Average image analysis software values included 17.4° version (3.5° difference, p < 0.0001), 9.2° inclination (3.9° difference, p < 0.001), and 74.2% for subluxation (18% difference, p < 0.0001). Conclusions Glenoid version and inclination values from the software and manual measurement on two-dimensional computed tomography were relatively similar, within approximately 4°. However, subluxation measurements differed by approximately 20%.


2016 ◽  
Vol 685 ◽  
pp. 857-862 ◽  
Author(s):  
Igor Skirnevskiy ◽  
Aleksandr Korovin

Recent research studies in the sphere of computer tomography are connected with the task of image analysis. Due to the fact that computed tomography images include artifacts, low contrast and different types of noises, researchers have to deal with a wide range of problems during the processing. There is a wide variety of preliminary processing methods which allow solving these problems. Obviously, the choice of these methods has a major impact on the result [1]. However, algorithm analysis of computed tomography images is not considered in the literature nowadays. This work presents an overview of the implementation approach of these methods.


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