scholarly journals Comparison of G-guide and Image-free Navigation System in Accuracy of Stem Anteversion Assessment During Total Hip Arthroplasty

2019 ◽  
Vol 13 (1) ◽  
pp. 109-116 ◽  
Author(s):  
Yuki Fujihara ◽  
Shigeo Fukunishi ◽  
Tomokazu Fukui ◽  
Shoji Nishio ◽  
Yu Takeda ◽  
...  
Keyword(s):  
Image Analysis ◽  
Navigation System ◽  
Measurement Accuracy ◽  
Femoral Stem ◽  
Reference Value ◽  
Image Analysis System ◽  
Measurement Systems ◽  
Comparative Accuracy ◽  
Ct Image Analysis ◽  
Analysis System

Introduction: We have developed and utilized the Gravity-guide (G-guide) as a simple manual instrument for intraoperative assessment and adjustment of stem anteversion (AV). Since 2013, we simultaneously measured stem AV using the G-guide and image-free navigation during THA procedure. The purpose of this study was to compare the measurement accuracy of the G-guide and navigation system using the postoperative CT results as a reference. Methods: In total, 59 hips in 56 patients who underwent primary THA using both the G-guide and image-free navigation system were included in the study. All patients underwent postoperative CT examination, and the femoral stem AV was assessed using a 3D image analysis system (Zed hip, LEXI, Japan). The AV angle derived from the postoperative CT image analysis was used as the reference value to assess the accuracy of the two intraoperative measurement systems. Results: The discrepancy between the G-guide and the postoperative CT-measured values averaged 5.0° ± 3.9°, while the corresponding value for the navigation system was 5.2° ± 4.1°. Acceptable accuracy with a measurement error of less than 10° was achieved in 86% and 90% of the cases for the G-guide and navigation measurements respectively. Conclusion: Consequently, it was shown that both navigation and G-guide measurements can achieve comparative accuracy and are clinically useful.

scholarly journals A Fully Automatic AI-based CT Image Analysis System for Accurate Detection, Diagnosis, and Quantitative Severity Evaluation of Pulmonary Tuberculosis

2021 ◽  
Author(s):  
Chenggong Yan ◽  
Lingfeng Wang ◽  
Jie Lin ◽  
Jun Xu ◽  
Tianjing Zhang ◽  
...  
Keyword(s):  
Image Analysis ◽  
Pulmonary Tuberculosis ◽  
Chest Ct ◽  
Ct Scans ◽  
Image Analysis System ◽  
Imaging Features ◽  
Ct Image ◽  
Pulmonary Tb ◽  
Ct Image Analysis ◽  
Analysis System

Abstract Background: Accurate and rapid diagnosis of pulmonary tuberculosis (TB) plays a crucial role in timely prevention and appropriate medical treatment to the disease. This study aims to develop and evaluate an artificial intelligence (AI)-based fully automated CT image analysis system for detection, diagnosis, and burden quantification of pulmonary TB.Methods: From December 2007 to September 2020, 892 chest CT scans from pathogen-confirmed TB patients were retrospectively included. A deep learning based cascading framework was connected to create a processing pipeline. To train and validate the model, 1921 lesions were manually labeled, classified by six categories of critical imaging features, and visually scored for the lesion involvement as the ground truth. “TB score” was calculated by the network-activation map to assess the disease burden quantitively. Independent test datasets from two additional hospitals and NIH TB Portal were used to validate externally the performance of the AI model.Results: CT scans from 526 participants (mean age, 48.5 years±16.5; 206 women) were analyzed. The lung lesion detection subsystem yielded a mean average precision of 0.68 on the validation cohort. In the independent datasets, the overall classification accuracy for six pulmonary critical imaging findings indicative of TB were 81.08%-91.05%. A moderate to strong correlation was demonstrated between the AI model quantified “TB score” and the radiologist-estimated CT score.Conclusion: This end-to-end AI system based on chest CT can achieve human-level diagnostic performance, and holds great potential for early management and medical resource optimization of patients with pulmonary TB in clinical practice.

scholarly journals An image analysis system for cervical cytology automation using nuclear DNA content.

1979 ◽  
Vol 27 (1) ◽  
pp. 613-620 ◽  
Author(s):  
J H Tucker
Keyword(s):  
Image Analysis ◽  
Measurement Accuracy ◽  
Nuclear Dna ◽  
Nuclear Dna Content ◽  
Cervical Cytology ◽  
Image Analysis System ◽  
Cell Nuclei ◽  
Computer Image Analysis ◽  
Integrated Optical ◽  
Analysis System

An experimental computer/image analysis system has been used to investigate cytology automation techniques based on nuclear DNA measurement and morphological artefact rejector tests. The system automatically measures and normalizes the integrated optical density of cell nuclei in specially prepared cervical cytology specimens, and selects any objects with abnormally high values for further analysis. These are then analyzed by morphological and densitometric tests designed to eliminate false positive signals caused by non-nuclear artefacts. The coordinates of the remaining abnormal nuclei are recorded so that they can subsequently be relocated and examined by a cytotechnician. Preliminary results are given showing the measurement accuracy of the system and the performance of the artefact rejection tests.

Chemical Classification and Particle Sizing of Foundry Sands

1985 ◽  
Vol 43 ◽  
pp. 388-389
Author(s):  
D.S. DeMiglio
Keyword(s):  
Image Analysis ◽  
Energy Dispersive Spectrometer ◽  
Image Analysis System ◽  
Representative Sampling ◽  
Foundry Sands ◽  
Large Atomic Number ◽  
Backscattered Electron ◽  
Sand Particles ◽  
Analysis System ◽  
Reclamation System

Much progress has been made in recent years towards the development of closed-loop foundry sand reclamation systems. However, virtually all work to date has determined the effectiveness of these systems to remove surface clay and metal oxide scales by a qualitative inspection of a representative sampling of sand particles. In this investigation, particles from a series of foundry sands were sized and chemically classified by a Lemont image analysis system (which was interfaced with an SEM and an X-ray energy dispersive spectrometer) in order to statistically document the effectiveness of a reclamation system developed by The Pangborn Company - a subsidiary of SOHIO.The following samples were submitted: unreclaimed sand; calcined sand; calcined & mechanically scrubbed sand and unused sand. Prior to analysis, each sample was sprinkled onto a carbon mount and coated with an evaporated film of carbon. A backscattered electron photomicrograph of a field of scale-covered particles is shown in Figure 1. Due to a large atomic number difference between sand particles and the carbon mount, the backscattered electron signal was used for image analysis since it had a uniform contrast over the shape of each particle.

SIGN IN Welcome!Log into your account your username your password Forgot your password Privacy policy PASSWORD RECOVERY Recover your password your email Struktol Home New fast measuring method for process optimization of sucrose crystallization New fast measuring method for process optimization of sucrose crystallization

2020 ◽  
pp. 49-52
Author(s):  
Trine Aabo Andersen
Keyword(s):  
Image Analysis ◽  
Process Optimization ◽  
Crystal Size ◽  
Measuring Method ◽  
Sieve Analysis ◽  
Image Analysis System ◽  
Line System ◽  
Non Invasive ◽  
Analysis System ◽  
User Friendly

A new fast measuring method for process optimization of sucrose crystallization using image analysis based on high quality images and algorithms is introduced. With the mobile, non-invasive at-line system all steps of the sucrose crystallization can be measured to determine the crystal size distribution. The image analysis system is easy to operate and is as well an efficient laboratory solution with user-friendly and customized software. In comparison to sieve analysis, image analyses performed with the ParticleTech Solution have been proven to be reliable.

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