Literature DB >> 10659737

Contralateral subtraction: a novel technique for detection of asymmetric abnormalities on digital chest radiographs.

Q Li1, S Katsuragawa, T Ishida, H Yoshida, S Tsukuda, H MacMahon, K Doi.   

Abstract

A novel contralateral subtraction technique has been developed to assist radiologists in the detection of asymmetric abnormalities on a single chest radiograph. With this method, the lateral inclination is first corrected by rotating and shifting the original chest image so that the midline of the thorax is aligned with the vertical centerline of the original chest image. The rotated image is then flipped laterally to produce a reversed "mirror" image. Finally, the mirror image is warped and subtracted from the original image for derivation of the contralateral subtraction image. The three key techniques which are employed in this study are applied successively to the initial contralateral subtraction technique for acquisition of improved subtraction images. One hundred PA chest radiographs, including 50 normals and 50 abnormals, were used as the database for this study. The percentage of chest images, which were rated as being adequate, good, or excellent quality of subtraction images by employing a subjective evaluation method, was improved from 73% to 91% by use of the three key techniques. The contralateral subtraction technique can be used for detection of any asymmetric abnormalities, such as lung nodules, pneumothorax, pneumonia, and emphysema, on a single chest radiograph, and therefore has potential utility in a high proportion of abnormal cases.

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Year:  2000        PMID: 10659737     DOI: 10.1118/1.598856

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  6 in total

1.  Utilization of computer-aided detection system in diagnosing unilateral maxillary sinusitis on panoramic radiographs.

Authors:  Yasufumi Ohashi; Yoshiko Ariji; Akitoshi Katsumata; Hiroshi Fujita; Miwa Nakayama; Motoki Fukuda; Michihito Nozawa; Eiichiro Ariji
Journal:  Dentomaxillofac Radiol       Date:  2016-02-03       Impact factor: 2.419

2.  Deformable image registration for temporal subtraction of chest radiographs.

Authors:  Min Li; Edward Castillo; Hong-Yan Luo; Xiao-Lin Zheng; Richard Castillo; Dmitriy Meshkov; Thomas Guerrero
Journal:  Int J Comput Assist Radiol Surg       Date:  2014-07       Impact factor: 2.924

3.  Effectiveness of temporal and dynamic subtraction images of the liver for detection of small HCC on abdominal CT images: comparison of 3D nonlinear image-warping and 3D global-matching techniques.

Authors:  Eiichiro Okumura; Shigeru Sanada; Masayuki Suzuki; Akihiro Takemura; Osamu Matsui
Journal:  Radiol Phys Technol       Date:  2011-01-13

4.  Computer-aided detection scheme for sentinel lymph nodes in lymphoscintigrams using symmetrical property around mapped injection point.

Authors:  Ryohei Nakayama; Akiyoshi Hizukuri; Koji Yamamoto; Nobuo Nakako; Naoki Nagasawa; Kan Takeda
Journal:  J Digit Imaging       Date:  2012-02       Impact factor: 4.056

5.  Performance of deep learning object detection technology in the detection and diagnosis of maxillary sinus lesions on panoramic radiographs.

Authors:  Ryosuke Kuwana; Yoshiko Ariji; Motoki Fukuda; Yoshitaka Kise; Michihito Nozawa; Chiaki Kuwada; Chisako Muramatsu; Akitoshi Katsumata; Hiroshi Fujita; Eiichiro Ariji
Journal:  Dentomaxillofac Radiol       Date:  2020-07-15       Impact factor: 2.419

6.  Smart spotting of pulmonary TB cavities using CT images.

Authors:  V Ezhil Swanly; L Selvam; P Mohan Kumar; J Arokia Renjith; M Arunachalam; K L Shunmuganathan
Journal:  Comput Math Methods Med       Date:  2013-12-03       Impact factor: 2.238

  6 in total

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