This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. This subproject is concerned with providing an automatic robust method for registering histological sections with MR images. The specific area for which this method will be optimized is the Medial Temporal Lobe (MTL). The goal in doing this is to use high-resolution MR and the registered histology to build detailed models of hippocampal anatomy and then to use these models to generate probabilistic labellings in vivo imaging data at standard structural resolution. Registering histology directly with MR is a difficult problem, because mounting and staining the tissue slice inevitably results in distortions of the underlying tissue. This means that the mapping from the stained sections to the high-resolution MR is both cross-contrast and non-linear. This is why, instead of attempting a direct approach to this problem, we have chosen to consider an intermediate step in the registration process, namely pre-registering the histology with the uncut block face images. This has several advantages, the most important being that the use of the block face images reduces the complexity of the problem, since one only needs to perform non-linear registration on 2D images.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Biotechnology Resource Grants (P41)
Project #
2P41RR014075-11
Application #
7957656
Study Section
Special Emphasis Panel (ZRG1-SBIB-L (40))
Project Start
2009-09-01
Project End
2010-05-31
Budget Start
2009-09-01
Budget End
2010-05-31
Support Year
11
Fiscal Year
2009
Total Cost
$130,849
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02199
Esch, Lorenz; Sun, Limin; Klüber, Viktor et al. (2018) MNE Scan: Software for real-time processing of electrophysiological data. J Neurosci Methods 303:55-67
Zaretskaya, Natalia; Fischl, Bruce; Reuter, Martin et al. (2018) Advantages of cortical surface reconstruction using submillimeter 7 T MEMPRAGE. Neuroimage 165:11-26
Lee, Jeungchan; Mawla, Ishtiaq; Kim, Jieun et al. (2018) Machine learning-based prediction of clinical pain using multimodal neuroimaging and autonomic metrics. Pain :
Ina Ly, K; Vakulenko-Lagun, Bella; Emblem, Kyrre E et al. (2018) Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI. Sci Rep 8:17062
Ellingsen, Dan-Mikael; Napadow, Vitaly; Protsenko, Ekaterina et al. (2018) Brain Mechanisms of Anticipated Painful Movements and Their Modulation by Manual Therapy in Chronic Low Back Pain. J Pain 19:1352-1365
Sawyer, Kayle S; Maleki, Nasim; Papadimitriou, George et al. (2018) Cerebral white matter sex dimorphism in alcoholism: a diffusion tensor imaging study. Neuropsychopharmacology 43:1876-1883
Lee, Jeungchan; Protsenko, Ekaterina; Lazaridou, Asimina et al. (2018) Encoding of Self-Referential Pain Catastrophizing in the Posterior Cingulate Cortex in Fibromyalgia. Arthritis Rheumatol 70:1308-1318
Cushing, Cody A; Im, Hee Yeon; Adams Jr., Reginald B et al. (2018) Neurodynamics and connectivity during facial fear perception: The role of threat exposure and signal congruity. Sci Rep 8:2776
Izen, Sarah C; Chrastil, Elizabeth R; Stern, Chantal E (2018) Resting State Connectivity Between Medial Temporal Lobe Regions and Intrinsic Cortical Networks Predicts Performance in a Path Integration Task. Front Hum Neurosci 12:415
Kang, Dong-Wha; Kim, Dongho; Chang, Li-Hung et al. (2018) Structural and Functional Connectivity Changes Beyond Visual Cortex in a Later Phase of Visual Perceptual Learning. Sci Rep 8:5186

Showing the most recent 10 out of 1099 publications