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Title: SU-E-I-75: Development of New Biological Fingerprints for Patient Recognition to Identify Misfiled Images in a PACS Server

Abstract

Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints that could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprintsmore » for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system because they are less affected by positioning differences during imaging.« less

Authors:
; ; ; ;  [1];  [2]
  1. Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, JP (Japan)
  2. Department of Health Sciences, Faculty of Medical Sciences, Kyushu University, Fukuoka, JP (Japan)
Publication Date:
OSTI Identifier:
22494019
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 42; Journal Issue: 6; Other Information: (c) 2015 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; BIOMEDICAL RADIOGRAPHY; IMAGES; LUNGS; MEDIASTINUM; PATIENTS; PERTURBED ANGULAR CORRELATION; RANDOMNESS

Citation Formats

Shimizu, Y, Yoon, Y, Iwase, K, Yasumatsu, S, Matsunobu, Y, and Morishita, J. SU-E-I-75: Development of New Biological Fingerprints for Patient Recognition to Identify Misfiled Images in a PACS Server. United States: N. p., 2015. Web. doi:10.1118/1.4924072.
Shimizu, Y, Yoon, Y, Iwase, K, Yasumatsu, S, Matsunobu, Y, & Morishita, J. SU-E-I-75: Development of New Biological Fingerprints for Patient Recognition to Identify Misfiled Images in a PACS Server. United States. doi:10.1118/1.4924072.
Shimizu, Y, Yoon, Y, Iwase, K, Yasumatsu, S, Matsunobu, Y, and Morishita, J. Mon . "SU-E-I-75: Development of New Biological Fingerprints for Patient Recognition to Identify Misfiled Images in a PACS Server". United States. doi:10.1118/1.4924072.
@article{osti_22494019,
title = {SU-E-I-75: Development of New Biological Fingerprints for Patient Recognition to Identify Misfiled Images in a PACS Server},
author = {Shimizu, Y and Yoon, Y and Iwase, K and Yasumatsu, S and Matsunobu, Y and Morishita, J},
abstractNote = {Purpose: We are trying to develop an image-searching technique to identify misfiled images in a picture archiving and communication system (PACS) server by using five biological fingerprints: the whole lung field, cardiac shadow, superior mediastinum, lung apex, and right lower lung. Each biological fingerprint in a chest radiograph includes distinctive anatomical structures to identify misfiled images. The whole lung field was less effective for evaluating the similarity between two images than the other biological fingerprints. This was mainly due to the variation in the positioning for chest radiographs. The purpose of this study is to develop new biological fingerprints that could reduce influence of differences in the positioning for chest radiography. Methods: Two hundred patients were selected randomly from our database (36,212 patients). These patients had two images each (current and previous images). Current images were used as the misfiled images in this study. A circumscribed rectangular area of the lung and the upper half of the rectangle were selected automatically as new biological fingerprints. These biological fingerprints were matched to all previous images in the database. The degrees of similarity between the two images were calculated for the same and different patients. The usefulness of new the biological fingerprints for automated patient recognition was examined in terms of receiver operating characteristic (ROC) analysis. Results: Area under the ROC curves (AUCs) for the circumscribed rectangle of the lung, upper half of the rectangle, and whole lung field were 0.980, 0.994, and 0.950, respectively. The new biological fingerprints showed better performance in identifying the patients correctly than the whole lung field. Conclusion: We have developed new biological fingerprints: circumscribed rectangle of the lung and upper half of the rectangle. These new biological fingerprints would be useful for automated patient identification system because they are less affected by positioning differences during imaging.},
doi = {10.1118/1.4924072},
journal = {Medical Physics},
number = 6,
volume = 42,
place = {United States},
year = {Mon Jun 15 00:00:00 EDT 2015},
month = {Mon Jun 15 00:00:00 EDT 2015}
}
  • Purpose: To introduce and investigate effective diameter ratios as a new patient metric for use in computed tomography protocol selection as a supplement to patient-specific size parameter data. Methods: The metrics of outer effective diameter and inner effective diameter were measured for 7 post-mortem subjects scanned with a standardized chest/abdomen/pelvis (CAP) protocol on a 320-slice MDCT scanner. The outer effective diameter was calculated by obtaining the anterior/posterior and lateral dimensions of the imaged anatomy at the middle of the scan range using Effective Diameter= SQRT(AP height*Lat Width). The inner effective diameter was calculated with the same equation using the APmore » and Lat dimensions of the anatomy excluding the adipose tissue. The ratio of outer to inner effective diameter was calculated for each subject. A relationship to BMI, weight, and CTDI conversion coefficients was investigated. Results: For the largest subject with BMI of 43.85 kg/m2 and weight of 255 lbs the diameter ratio was calculated as 1.33. For the second largest subject with BMI of 33.5 kg/m2 and weight of 192.4 lbs the diameter ratio was measured as 1.43, indicating a larger percentage of adipose tissue in the second largest subject’s anatomical composition. For the smallest subject at BMI of 17.4 kg/m2 and weight of 86 lbs a similar tissue composition was indicated as a subject with BMI of 24.2 kg/m2 and weight of 136 lbs as they had the same diameter ratios of 1.11. Conclusion: The diameter ratio proves to contain information about anatomical composition that the BMI and weight alone do not. The utility of this metric is still being examined but could prove useful for determining MDCT techniques and for giving a more in depth detail of the composition of a patient’s body habitus.« less
  • Purpose: The purpose of this work is to develop a new patient set-up monitoring system using force sensing resistor (FSR) sensors that can confirm pressure of contact surface and evaluate its feasibility. Methods: In this study, we focused on develop the patient set-up monitoring system to compensate for the limitation of existing optical based monitoring system, so the developed system can inform motion in the radiation therapy. The set-up monitoring system was designed consisting of sensor units (FSR sensor), signal conditioning devices (USB cable/interface electronics), a control PC, and a developed analysis software. The sensor unit was made by attachingmore » FSR sensor and dispersing pressure sponge to prevent error which is caused by concentrating specific point. Measured signal from the FSR sensor was sampled to arduino mega 2560 microcontroller, transferred to control PC by using serial communication. The measured data went through normalization process. The normalized data was displayed through the developed graphic user interface (GUI) software. The software was designed to display a single sensor unit intensity (maximum 16 sensors) and display 2D pressure distribution (using 16 sensors) according to the purpose. Results: Changes of pressure value according to motion was confirmed by the developed set-up monitoring system. Very small movement such as little physical change in appearance can be confirmed using a single unit and using 2D pressure distribution. Also, the set-up monitoring system can observe in real time. Conclusion: In this study, we developed the new set-up monitoring system using FSR sensor. Especially, we expect that the new set-up monitoring system is suitable for motion monitoring of blind area that is hard to confirm existing optical system and compensate existing optical based monitoring system. As a further study, an integrated system will be constructed through correlation of existing optical monitoring system. This work was supported by the Industrial R&D program of MOTIE/KEIT. [10048997, Development of the core technology for integrated therapy devices based on real-time MRI guided tumor tracking] and the Mid-career Researcher Program (2014R1A2A1A10050270) through the National Research Foundation of Korea funded by the Ministry of Science, ICT&Future Planning.« less
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