回顾:胸部前后片结节分割的研究。

IF 3.3 Q2 ENGINEERING, BIOMEDICAL
International Journal of Biomedical Imaging Pub Date : 2018-10-18 eCollection Date: 2018-01-01 DOI:10.1155/2018/9752638
S K Chaya Devi, T Satya Savithri
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引用次数: 4

摘要

肺癌是世界上主要的癌症类型之一。如果能及早发现这种疾病,可以提高生存率。胸部后路和前路x线摄影和计算机断层扫描是检测肺部肿瘤最常用的诊断技术。胸部后路和前路x线摄影需要较少的辐射剂量,在大多数诊断中心都可以获得,与其他诊断技术相比,它的成本更低。因此,PA胸片成为肺癌检测中最常用的技术。由于图像中存在重叠的解剖结构,有时放射科医生无法从图像中发现异常。为了帮助放射科医生从胸片图像中诊断肿瘤,CAD方案的范围已经发展了三十年。这些计算机化的工具可能被放射科医生用作检测肿瘤的第二意见。本文综述了从胸部图像中检测肿瘤的相关文献。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Review: On Segmentation of Nodules from Posterior and Anterior Chest Radiographs.

Review: On Segmentation of Nodules from Posterior and Anterior Chest Radiographs.

Review: On Segmentation of Nodules from Posterior and Anterior Chest Radiographs.

Review: On Segmentation of Nodules from Posterior and Anterior Chest Radiographs.

Lung cancer is one of the major types of cancer in the world. Survival rate can be increased if the disease can be identified early. Posterior and anterior chest radiography and computerized tomography scans are the most used diagnosis techniques for detecting tumor from lungs. Posterior and anterior chest radiography requires less radiation dose and is available in most of the diagnostic centers and it costs less compared to the remaining diagnosis techniques. So PA chest radiography became the most commonly used technique for lung cancer detection. Because of superimposed anatomical structures present in the image, sometimes radiologists cannot find abnormalities from the image. To help radiologists in diagnosing tumor from PA chest radiographic images range of CAD scheme has been developed for the past three decades. These computerized tools may be used by radiologists as a second opinion in detecting tumor. Literature survey on detecting tumors from chest graphs is presented in this paper.

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来源期刊
CiteScore
12.00
自引率
0.00%
发文量
11
审稿时长
20 weeks
期刊介绍: The International Journal of Biomedical Imaging is managed by a board of editors comprising internationally renowned active researchers. The journal is freely accessible online and also offered for purchase in print format. It employs a web-based review system to ensure swift turnaround times while maintaining high standards. In addition to regular issues, special issues are organized by guest editors. The subject areas covered include (but are not limited to): Digital radiography and tomosynthesis X-ray computed tomography (CT) Magnetic resonance imaging (MRI) Single photon emission computed tomography (SPECT) Positron emission tomography (PET) Ultrasound imaging Diffuse optical tomography, coherence, fluorescence, bioluminescence tomography, impedance tomography Neutron imaging for biomedical applications Magnetic and optical spectroscopy, and optical biopsy Optical, electron, scanning tunneling/atomic force microscopy Small animal imaging Functional, cellular, and molecular imaging Imaging assays for screening and molecular analysis Microarray image analysis and bioinformatics Emerging biomedical imaging techniques Imaging modality fusion Biomedical imaging instrumentation Biomedical image processing, pattern recognition, and analysis Biomedical image visualization, compression, transmission, and storage Imaging and modeling related to systems biology and systems biomedicine Applied mathematics, applied physics, and chemistry related to biomedical imaging Grid-enabling technology for biomedical imaging and informatics
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