A multi-atlas based method for automated anatomical Macaca fascicularis brain MRI segmentation and PET kinetic extraction

Ballanger, Bénédicte; Tremblay, Léon; Sgambato-Faure, Véronique; Beaudoin-Gobert, Maude; Lávenne, F.; Bars, Didier Le; Costes, Nicolas

doi:10.1016/j.neuroimage.2013.03.029

Cited by 49 publications

(39 citation statements)

References 41 publications

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“…Moreover, previous PET studies with test-retest data have shown a good reproducibility of radiotracer binding measurement (Costes et al, 2007; Ballanger et al, 2013). …”

Section: Methodsmentioning

confidence: 83%

“…Reconstructed volumes were 128 × 128 matrices of 0.32 × 0.32 mm 2 pixels in sixty-three 2.42 mm spaced planes. The extraction of tissue time-activity concentration curves from automated delineated regions of interest was made possible by the specific Macaca fascicularis brain atlas (Ballanger et al, 2013). The influx rate constant of 18 F-DOPA (Ki) was calculated by linearization of the graphical Patlak plot (Patlak et al, 1983) over 90 min post-injection using the cerebellum as the reference region.…”

Section: Methodsmentioning

confidence: 99%

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Social behavioral changes in MPTP-treated monkey model of Parkinson's disease

Durand¹,

Petit

Tremblay

et al. 2015

Front. Behav. Neurosci.

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Parkinsonian patients experience not only the physical discomfort of motor disorders but also the considerable psychological distress caused by cognitive deficits and behavioral disorders. These two factors can result in a disruption of social relationships during the symptomatic and even the presymptomatic motor states of the disease. However, it remains difficult, if not impossible, to evaluate social relationships in presymptomatic patients. The present study focused on the evaluation of social relationships within a group of female long-tailed macaques during presymptomatic and symptomatic motor states induced by Chronic Low-Dose (CLD) and then Chronic High-Dose (CHD) systemic administration of 1-methyl-4-phenyl-l,2,3,6-tetrahydropyridine (MPTP). Dopaminergic denervation within basal ganglia and cortical areas was evaluated using Positron Emission Tomography (PET) scans with 18F-DOPA (6-[18F]-fluoro-L-3,4-dihydroxyphenylalanine) radiotracer. Interestingly, social behavioral changes could be identified in the presymptomatic motor state before any motor and/or cognitive impairment occurred. Stronger effects were observed in subordinate animals compared to dominant animals. From baseline state to CLD-presymptomatic motor state, the frequency of emitted affiliative and aggressive behaviors increased. From CLD-presymptomatic to CHD-presymptomatic motor states, the frequency of the three categories of social behaviors (aggressive, submissive and affiliative) decreased. At this time, quantitative data analysis in PET scans highlighted a dopaminergic denervation in the insula and the posterior caudate nucleus. Finally, the frequency of the three categories of social behaviors decreased during the stable-symptomatic motor state compared to baseline and presymptomatic motor states; this was also associated with motor and cognitive disorders and a dopaminergic denervation in all the evaluated cortical and subcortical structures.

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“…Moreover, previous PET studies with test-retest data have shown a good reproducibility of radiotracer binding measurement (Costes et al, 2007; Ballanger et al, 2013). …”

Section: Methodsmentioning

confidence: 83%

Section: Methodsmentioning

confidence: 99%

Social behavioral changes in MPTP-treated monkey model of Parkinson's disease

Durand¹,

Petit

Tremblay

et al. 2015

Front. Behav. Neurosci.

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“…MAS has also been employed for the segmentation of cortical and subcortical structures in MRI data from fetuses, neonates, and infants too (Gholipour et al, 2012; Gousias et al, 2008, 2010, 2013; Shi et al, 2010; Wang et al, 2014e; Li et al, 2014; Koch et al, 2014; Makropoulos et al, 2014; Wang et al, 2014d), in which the contrast inversion due to ongoing myelination complicates the segmentation. Another area of application of MAS has been the segmentation of brain MRI in animal studies, e.g., mice (Da et al, 2012; Ma et al, 2014; Nie and Shen, 2013; Lee et al, 2014a; Khan et al, 2014), rats (Lancelot et al, 2014) and non-human primates (Ballanger et al, 2013). Finally, there are also studies that have applied MAS to the analysis of diffusion brain MRI data of humans (Jin et al, 2012; Tang et al, 2014; Traynor et al, 2010), which requires specific strategies for the registration, atlas selection and label fusion steps, due to the nature of the data, which are typically described by directional functions defined on the sphere at each voxel.…”

Section: Survey Of Applicationsmentioning

confidence: 99%

Multi-atlas segmentation of biomedical images: A survey

Iglesias

Sabuncu

2015

Medical Image Analysis

591

457

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Multi-atlas segmentation (MAS), first introduced and popularized by the pioneering work of Rohlfing, Brandt, Menzel and Maurer Jr (2004), Klein, Mensh, Ghosh, Tourville and Hirsch (2005), and Heckemann, Hajnal, Aljabar, Rueckert and Hammers (2006), is becoming one of the most widely-used and successful image segmentation techniques in biomedical applications. By manipulating and utilizing the entire dataset of “atlases” (training images that have been previously labeled, e.g., manually by an expert), rather than some model-based average representation, MAS has the flexibility to better capture anatomical variation, thus offering superior segmentation accuracy. This benefit, however, typically comes at a high computational cost. Recent advancements in computer hardware and image processing software have been instrumental in addressing this challenge and facilitated the wide adoption of MAS. Today, MAS has come a long way and the approach includes a wide array of sophisticated algorithms that employ ideas from machine learning, probabilistic modeling, optimization, and computer vision, among other fields. This paper presents a survey of published MAS algorithms and studies that have applied these methods to various biomedical problems. In writing this survey, we have three distinct aims. Our primary goal is to document how MAS was originally conceived, later evolved, and now relates to alternative methods. Second, this paper is intended to be a detailed reference of past research activity in MAS, which now spans over a decade (2003 – 2014) and entails novel methodological developments and application-specific solutions. Finally, our goal is to also present a perspective on the future of MAS, which, we believe, will be one of the dominant approaches in biomedical image segmentation.

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“…This is a useful strategy to improve the robustness and accuracy of atlas-based segmentation. 11,[13][14][15][16][17][18][19][20][21][22] It is particularly effective and efficient when there are multiple images with manual labeling available as atlases such as in brain MR segmentation [15][16][17][18][19][20] and cardiac image segmentation. 11,17,21 Rohlfing et al 13 and Rohlfing and Maurer 14 studied different atlas ranking and selection methods for MAS and showed that the intensity-based similarity metrics between the warped atlas image and the target image were good criteria for atlas selection.…”

Section: A Challenges and Related Workmentioning

confidence: 99%