Importance of Volumetric Measurement Processes in Oncology Imaging Trials for Screening and Evaluation of Tumors as Per Response Evaluation Criteria in Solid Tumors

Vemuri, Ravichandra; Jarecha, Rudresh; Hwi, Kim Kah; Gundamaraju, Rohit; MaruthiKanth, Aripaka; Kulkarni, AravindRao; Reddy, Sundeep

doi:10.7314/apjcp.2014.15.5.2375

Cited by 3 publications

(1 citation statement)

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“…Almost 57% (8 million) of new cancer cases, 65% (5.3 million) of the cancer deaths and 48% (15.6 million) of the 5-year prevalent cancer cases occurred in the less developed regions (Globocan, 2012a). Therefore, because of high incidence, mortality and burden costs of cancer disease, there is an urgent need for early detection strategies (Mohammadzadeh and Safdari, 2014;Vemuri et al, 2014;Azadmanjir et al, 2015;Shridhar et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Advances in Optimal Detection of Cancer by Image Processing; Experience with Lung and Breast Cancers

Mohammadzadeh

Safdari²,

Ghazisaeidi³

et al. 2015

Asian Pacific Journal of Cancer Prevention

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Clinicians should looking for techniques that helps to early diagnosis of cancer, because early cancer detection is critical to increase survival and cost effectiveness of treatment, and as a result decrease mortality rate. Medical images are the most important tools to provide assistance. However, medical images have some limitations for optimal detection of some neoplasias, originating either from the imaging techniques themselves, or from human visual or intellectual capacity. Image processing techniques are allowing earlier detection of abnormalities and treatment monitoring. Because the time is a very important factor in cancer treatment, especially in cancers such as the lung and breast, imaging techniques are used to accelerate diagnosis more than with other cancers. In this paper, we outline experience in use of image processing techniques for lung and breast cancer diagnosis. Looking at the experience gained will help specialists to choose the appropriate technique for optimization of diagnosis through medical imaging.

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Section: Introductionmentioning

confidence: 99%