Computer-aided diagnosis for detection of changes in sequential chest radiographs (in Japanese)

被引:0
|
作者
Sanada, S [1 ]
机构
[1] Kanazawa Univ, Sch Hlth Sci, Kanazawa, Ishikawa 9200942, Japan
关键词
D O I
10.1118/1.598810
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
The subtraction image of digital chest radiographs taken at different times improved the diagnostic accuracy of radiologists viewing screening chest radiographs. The accurate registration of two chest images using “lung markings” instead of “rib edges” enables us to detect subtle changes in the “difference image.” The “lung markings” are the shadows of blood vessels traversing lung substance. Most of the morbid changes grow in lung substance not in the rib cage. Twenty-nine pairs of posteroanterior chest radiographs with and without temporal morbid changes were selected from approximately 200 sequential cases. The images were 1760×1760 matrix and 1024 gray scale with a computed radiography system (Fuji Medical System, Tokyo). Image registration employed the matching of “lung markings” in the two radiographs. Observer performance tests with and without the use of the “difference image” were carried out by eight radiologists. Six of the eight observers diagnosed with higher sensitivity. The mean for eight observers increased from 43.9% to 55.3% with a statistical significance of [formula omitted] The mean area under the AFROC (Alternative Free-Response Receiver Operating Characteristics) curve improved from 0.596 to 0.647 with a statistical significance of [formula omitted] The false positive response was comparable with and without the use of the subtraction image. We conclude that the use of the subtraction image with the new registration technique improves the diagnostic accuracy for detection of subtle changes between radiographs, such as nodule, infiltrate, and cardiomegaly of radiographic findings. © 1999, American Association of Physicists in Medicine. All rights reserved.
引用
收藏
页码:2708 / 2708
页数:1
相关论文
共 50 条
  • [41] Computer-aided diagnosis scheme for interstitial lung diseases on chest radiographs with artificial neural networks
    Ishida, T
    Katsuragawa, S
    MacMahon, H
    Doi, K
    RADIOLOGY, 1996, 201 : 520 - 520
  • [42] IMAGE FEATURE ANALYSIS FOR COMPUTER-AIDED DIAGNOSIS - ACCURATE DETERMINATION OF RIBCAGE BOUNDARY IN CHEST RADIOGRAPHS
    XU, XW
    DOI, K
    MEDICAL PHYSICS, 1995, 22 (05) : 617 - 626
  • [43] Catheter Detection and Classification on Chest Radiographs: An automated prototype computer-aided detection (CAD) system for radiologists
    Ramakrishna, Bharath
    Brown, Matthew
    Goldin, Jonathan
    Cagnon, Chris
    Enzmann, Dieter
    MEDICAL IMAGING 2011: COMPUTER-AIDED DIAGNOSIS, 2011, 7963
  • [44] Lung cancers missed on chest radiographs: Results obtained with a commercial computer-aided detection program
    Li, Feng
    Engelmann, Roger
    Metz, Charles E.
    Doi, Kunio
    MacMahon, Heber
    RADIOLOGY, 2008, 246 (01) : 273 - 280
  • [45] Evaluation of the feasibility of explainable computer-aided detection of cardiomegaly on chest radiographs using deep learning
    Lee, Mu Sook
    Kim, Yong Soo
    Kim, Minki
    Usman, Muhammad
    Byon, Shi Sub
    Kim, Sung Hyun
    Lee, Byoung Il
    Lee, Byoung-Dai
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [46] Computer-aided Abnormality Detection in Chest Radiographs in a Clinical Setting via Domain-adaptation
    Dubey, Abhishek K.
    Young, Michael T.
    Stanley, Christopher
    Lunga, Dalton
    Hinkle, Jacob
    BIOIMAGING: PROCEEDINGS OF THE 14TH INTERNATIONAL JOINT CONFERENCE ON BIOMEDICAL ENGINEERING SYSTEMS AND TECHNOLOGIES - VOL. 2: BIOIMAGING, 2021, : 65 - 72
  • [47] Evaluation of the feasibility of explainable computer-aided detection of cardiomegaly on chest radiographs using deep learning
    Mu Sook Lee
    Yong Soo Kim
    Minki Kim
    Muhammad Usman
    Shi Sub Byon
    Sung Hyun Kim
    Byoung Il Lee
    Byoung-Dai Lee
    Scientific Reports, 11
  • [48] Accuracy of CAD4TB (Computer-Aided Detection for Tuberculosis) on paediatric chest radiographs
    Edem, Victory Fabian
    Nkereuwem, Esin
    Agbla, Schadrac C.
    Owusu, Sheila A.
    Sillah, Abdou K.
    Saidy, Binta
    Jallow, Musa B.
    Forson, Audrey G.
    Egere, Uzochukwu
    Kampmann, Beate
    Togun, Toyin
    EUROPEAN RESPIRATORY JOURNAL, 2024, 64 (05)
  • [49] Computer Aided Diagnosis of Pleural Effusion in Tuberculosis Chest Radiographs
    Sharma, Utkarsh
    Lall, Brejesh
    IMAGE ANALYSIS AND PROCESSING,(ICIAP 2017), PT I, 2017, 10484 : 617 - 625
  • [50] Effect of a computer-aided diagnosis scheme on radiologists' performance in detection of lung nodules on radiographs
    Kobayashi, T
    Xu, XW
    MacMahon, H
    Metz, CE
    Doi, K
    RADIOLOGY, 1996, 199 (03) : 843 - 848