Multimodality imaging combination in small animal via point-based registration

Yang, Ching-Ching; Wu, Tung Hsin; Meng, Lin; Huang, Yen‐Hua; Guo, Wan Yuo; Chen, C.L.; Wang, T.C.; Yin, Wei Hsian; Lee, J.S.

doi:10.1016/j.nima.2006.08.045

Cited by 5 publications

(5 citation statements)

References 6 publications

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“…Our challenge was to design a coregistration tool that could be put inside the imaging cell between the animal and the bed [8,9] and that could be detected in 3 modalities: CT, SPECT and MRI. It is fast enough and does not extend our protocols duration.…”

Section: Discussionmentioning

confidence: 99%

Coregistration of datasets from a micro-SPECT/CT and a preclinical 1.5T MRI

Dillenseger

Guillaud²,

Goetz

et al. 2013

Nuclear Instruments and Methods in Physics Research Section A:

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Section: Discussionmentioning

confidence: 99%

Coregistration of datasets from a micro-SPECT/CT and a preclinical 1.5T MRI

Dillenseger

Guillaud²,

Goetz

et al. 2013

Nuclear Instruments and Methods in Physics Research Section A:

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“…To analyze the coregistration accuracy, we calculated the fiducial registration error (FRE) and the target registration error (TRE) 18,19 [ Fig . The TRE is the distance, measured after registration, between a reference corresponding point other than fiducial points used for coregistration.…”

Section: Experimental Protocolsmentioning

confidence: 99%

“…Many studies have focused on the evaluation of multimodal registration methods. 6,9,14,19 These studies mainly discuss and compare algorithms and methodological aspects of different registration methods and do not evaluate the impact of animal movements on the registration accuracy. Our study aimed at evaluating animal intrinsic (IIIa) and extrinsic (IIIb) movements during long imaging protocols (>30 min).…”

Section: Accuracy Of Fiducial and Target Coregistrationmentioning

confidence: 99%

Estimation of subject coregistration errors during multimodal preclinical imaging using separate instruments: origins and avoidance of artifacts

et al. 2017

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We use high-resolution [Formula: see text] data in multiple experiments to estimate the sources of error during coregistration of images acquired on separate preclinical instruments. In combination with experiments with phantoms, we completed imaging on mice, aimed at identifying the possible sources of registration errors, caused either by transport of the animal, movement of the animal itself, or methods of coregistration. The same imaging cell was used as a holder for phantoms and animals. For all procedures, rigid coregistration was carried out using a common landmark coregistration system, placed inside the imaging cell. We used the fiducial registration error and the target registration error to analyze the coregistration accuracy. We found that moving an imaging cell between two preclinical devices during a multimodal procedure gives an error of about [Formula: see text] at most. Therefore, it could not be considered a source of coregistration errors. Errors linked to spontaneous movements of the animal increased with time, to nearly 1 mm at most, excepted for body parts that were properly restrained. This work highlights the importance of animal intrinsic movements during a multiacquisition procedure and demonstrates a simple method to identify and quantify the sources of error during coregistration.

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“…Image registration methods have been widely used both in human medicine [6][7][8][9][10][11] and preclinical studies [12][13][14][15][16][17][18] to improve matching between images acquired on different modalities such as PET and MR, 19 SPECT and CT, 20 and PET and CT. 21 Registration approaches applied to humans are also suitable for companion animals. [22][23][24][25][26][27][28][29][30][31] and may prove useful in comparative oncology, which refers to the study of cancer etiology, biology, and treatment in companion FIG.…”

Section: Introductionmentioning

confidence: 99%

“…Image registration methods have been widely used both in human medicine and preclinical studies to improve matching between images acquired on different modalities such as PET and MR, SPECT and CT, and PET and CT . Registration approaches applied to humans are also suitable for companion animals .…”

Section: Introductionmentioning

confidence: 99%

Invited Review—image Registration in Veterinary Radiation Oncology: Indications, Implications, and Future Advances

Feng

Lawrence

Cheng

et al. 2016

Vet Radiology Ultrasound

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The field of veterinary radiation therapy (RT) has gained substantial momentum in recent decades with significant advances in conformal treatment planning, image-guided radiation therapy (IGRT), and intensity-modulated (IMRT) techniques. At the root of these advancements lie improvements in tumor imaging, image alignment (registration), target volume delineation, and identification of critical structures. Image registration has been widely used to combine information from multimodality images such as computerized tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) to improve the accuracy of radiation delivery and reliably identify tumor-bearing areas. Many different techniques have been applied in image registration. This review provides an overview of medical image registration in RT and its applications in veterinary oncology. A summary of the most commonly used approaches in human and veterinary medicine is presented along with their current use in IGRT and adaptive radiation therapy (ART). It is important to realize that registration does not guarantee that target volumes, such as the gross tumor volume (GTV), are correctly identified on the image being registered, as limitations unique to registration algorithms exist. Research involving novel registration frameworks for automatic segmentation of tumor volumes is ongoing and comparative oncology programs offer a unique opportunity to test the efficacy of proposed algorithms.

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Multimodality imaging combination in small animal via point-based registration

Cited by 5 publications

References 6 publications

Coregistration of datasets from a micro-SPECT/CT and a preclinical 1.5T MRI

Coregistration of datasets from a micro-SPECT/CT and a preclinical 1.5T MRI

Estimation of subject coregistration errors during multimodal preclinical imaging using separate instruments: origins and avoidance of artifacts

Invited Review—image Registration in Veterinary Radiation Oncology: Indications, Implications, and Future Advances

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