2017
DOI: 10.1016/j.cmpb.2017.07.006
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Hybrid PET/MRI co-segmentation based on joint fuzzy connectedness and graph cut

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Cited by 11 publications
(3 citation statements)
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“…Positron emission tomography can show the pathophysiologic characteristics of the lesion, and it is easier to find the lesion. However, radioactive tracers with high radiation are used in positron emission tomographic scans, 6,7 and inflammatory cells such as neutrophils in areas of inflammation will also accumulate the tracers. Conventional US provides a lot of useful information about tumors such as the tumor structure, blood supply, surrounding infiltration, and lymph node metastasis, but it lacks information on hardness.…”
mentioning
confidence: 99%
“…Positron emission tomography can show the pathophysiologic characteristics of the lesion, and it is easier to find the lesion. However, radioactive tracers with high radiation are used in positron emission tomographic scans, 6,7 and inflammatory cells such as neutrophils in areas of inflammation will also accumulate the tracers. Conventional US provides a lot of useful information about tumors such as the tumor structure, blood supply, surrounding infiltration, and lymph node metastasis, but it lacks information on hardness.…”
mentioning
confidence: 99%
“…Research is needed to further explore whether the threshold is related to additional tumor-related factors such as hypoxia, proliferation, and histological differences. Despite ongoing innovations [ 65 , 66 , 75 ], errors in automatically delineated target areas may still occur due to imprecise tumor boundaries, necessitating manual adjustments.…”
Section: Radiotherapy Planningmentioning
confidence: 99%
“…However, a one-to-one relationship between anatomical and functional images is not always appropriate [38]. When PET/CT or PET/MRI imaging is employed, BTV delineation should be obtained avoiding the use of the anatomical information provided by CT and MRI measurements or alternatively, the latter should be used very carefully [49]. For example, Yezzi et al [50] proposed ACs to simultaneously segment and register features from multimodal images.…”
Section: Introductionmentioning
confidence: 99%