Main Page/SlicerCommunity/2015 - Revision history

Marianna: /* Hippocampal Volume is Reduced in Schizophrenia and Schizoaffective Disorder but not in Psychotic Bipolar I Disorder Demonstrated by Both Manual Tracing and Automated Parcellation (Freesurfer) */

2020-02-12T16:19:00Z

Hippocampal Volume is Reduced in Schizophrenia and Schizoaffective Disorder but not in Psychotic Bipolar I Disorder Demonstrated by Both Manual Tracing and Automated Parcellation (Freesurfer)

Marianna: /* Isometric Scaling in Developing Long Bones Is Achieved by an Optimal Epiphyseal Growth Balance */

2020-02-12T16:15:59Z

Isometric Scaling in Developing Long Bones Is Achieved by an Optimal Epiphyseal Growth Balance

Marianna at 20:10, 11 February 2020

2020-02-11T20:10:39Z

Marianna at 20:05, 11 February 2020

2020-02-11T20:05:37Z

Marianna: /* A Multidimensional Dynamic Quantification Tool for the Mitral Valve */

2020-02-11T18:43:53Z

A Multidimensional Dynamic Quantification Tool for the Mitral Valve

Marianna: /* Two-Center Prospective, Randomized, Clinical, and Radiographic Study Comparing Osteotome Sinus Floor Elevation with or without Bone Graft and Simultaneous Implant Placement */

2020-02-11T18:43:32Z

Two-Center Prospective, Randomized, Clinical, and Radiographic Study Comparing Osteotome Sinus Floor Elevation with or without Bone Graft and Simultaneous Implant Placement

Marianna: /* Reduced Bone Density and Vertebral Fractures in Smokers. Men and COPD Patients at Increased Risk */

2020-02-11T16:53:37Z

Reduced Bone Density and Vertebral Fractures in Smokers. Men and COPD Patients at Increased Risk

Marianna at 16:51, 11 February 2020

2020-02-11T16:51:23Z

Marianna: /* Optimizing Parameters of an Open-source Airway Segmentation Algorithm using Different CT Images */

2020-02-11T16:49:40Z

Optimizing Parameters of an Open-source Airway Segmentation Algorithm using Different CT Images

Marianna: /* Isometric Scaling in Developing Long Bones Is Achieved by an Optimal Epiphyseal Growth Balance */

2020-02-11T16:49:12Z

Isometric Scaling in Developing Long Bones Is Achieved by an Optimal Epiphyseal Growth Balance

← Older revision		Revision as of 16:19, 12 February 2020
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		+	==Algorithm For Simulation Of Craniotomies Assisted By Peripheral For 3D Virtual Navigation==
		+
		+	{\| width="100%"
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		+	'''Publication:''' [https://www.ncbi.nlm.nih.gov/pubmed/26737914 Conf Proc IEEE Eng Med Biol Soc. 2015;2015:7043-6. PMID: 26737914]
		+
		+	'''Authors:''' Duque SI, Ochoa JF, Botero AF, Ramirez M.
		+
		+	'''Institution:''' Bioinstrumentation and Clinical Research Group, Bioengineering Program, Universidad de Antioquia UdeA, Medellin, Colombia.
		+
		+	'''Abstract:'''
		+	Neurosurgical procedures require high precision and an accurate localization of the structures. For that reason and due to the advances in 3D visualization, the software for planning and training neurosurgeries has become an important tool for neurosurgeons and students, but the manipulation of the 3D structures is not always easy for the staff that usually works with 2D images. This paper describes a system developed in open source software that allows performing a virtual craniotomy (a common procedure in neurosurgery that enables the access to intracranial lesions) in [http://www.slicer.org '''3D Slicer''']; the system includes a peripheral input in order to permit the manipulation of the 3D structures according to camera movements and to guide the movement of the craniotomy tool.
		+	\|}

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 * R01 HL089897/HL/NHLBI NIH HHS/United States
 * R01 HL089856/HL/NHLBI NIH HHS/United States
 |}

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-Go to <big>[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2020 2020] ::  [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2020 2020] :: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2019 2019]  ::
+Go to <big>[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2020 2020] ::  [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2019 2019]  ::
 [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2018 2018]  ::
-[https://www.slicer.org/wiki/Main_Page/SlicerCommunity-2017 2017] ::
+[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2017 2017] ::
-[https://www.slicer.org/wiki/Main_Page/SlicerCommunity-2016 2016] ::
+[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2016 2016] ::
-[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2015 2015] :: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2011-2014 2014-2011]] :: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2005-2010  2010-2005]]</big>
+[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2015 2015] :: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2011-2014 2014-2011]:: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2005-2010  2010-2005]</big>
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-Go to <big>[https://www.slicer.org/wiki/Main_Page/SlicerCommunity 2017] ::  [https://www.slicer.org/wiki/Main_Page/SlicerCommunity-2016 2016]:: [[Main_Page/SlicerCommunity-2015|2015]] :: [[Main_Page/SlicerCommunity-2011-2014|2014-2011]] :: [[Main_Page/SlicerCommunity-2005-2010|2010-2005]]</big>
+Go to <big>[https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2020 2020] ::  [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2020 2020] :: [https://www.slicer.org/wiki/Main_Page/SlicerCommunity/2019 2019]  ::
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← Older revision		Revision as of 18:43, 11 February 2020
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	In the first four examples, the segmentation performed well. In the next two examples (third and fourth rows), applying a smoothing filter improved the segmentation result due to reduced CSF volume and image artifacts. The semi-automated segmentation method requires initial user input to approximate the center of the non-segmented spinal cord, between the start and end points of the desired segmentation region, using [http://www.slicer.org '''3D Slicer'''].]]		In the first four examples, the segmentation performed well. In the next two examples (third and fourth rows), applying a smoothing filter improved the segmentation result due to reduced CSF volume and image artifacts. The semi-automated segmentation method requires initial user input to approximate the center of the non-segmented spinal cord, between the start and end points of the desired segmentation region, using [http://www.slicer.org '''3D Slicer'''].]]
		+	\|}
		+
		+	==Two-Center Prospective, Randomized, Clinical, and Radiographic Study Comparing Osteotome Sinus Floor Elevation with or without Bone Graft and Simultaneous Implant Placement==
		+
		+	{\|width="100%"
		+	\|
		+	'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/26315564 Clin Implant Dent Relat Res. 2016 Oct;18(5):873-882. PMID: 26315564] \| [http://onlinelibrary.wiley.com/doi/10.1111/cid.12373/epdf PDF]
		+
		+	'''Authors:''' Marković A, Mišić T, Calvo-Guirado JL, Delgado-Ruíz RA, Janjić B, Abboud M.
		+
		+	'''Institution:''' Clinic of Oral Surgery, School of Dental Medicine, University of Belgrade, Belgrade, Serbia.
		+
		+	'''Background/Purpose:''' To evaluate stability and success rate of hydrophilic nanostructured implants placed via osteotome sinus floor elevation (OSFE) without grafting material or using β-tricalcium phosphate (β-TCP), deproteinized bovine bone (DBB), or their combination, and also to assess three-dimensional volumetric stability of endo-sinus bone gained in the aforementioned conditions.
		+	Materials and Methods: OSFE with simultaneous implant placement (10-mm long SLActive-BL® , Straumann, Basel, Switzerland) was performed. Grafting materials were randomly allocated to implant sites, whereas one site was left without graft. Implant stability was measured by resonance frequency analysis over 6 months. Implant success was evaluated after 2 years of loading. Volume of new endo-sinus bone was calculated from CBCT images using [http://slicer.org '''3D Slicer'''] software. Results: A total of 180 implants were inserted into posterior maxilla of 45 patients with 6.59 ± 0.45 mm of residual bone height, and all remained successful after 2 years. Implant stability steadily increased during healing, without significant difference between groups (p = .658). After 2 years, endo-sinus bone significantly shrank (p < .001) in all groups (DBB:66.34%; β-TCP:61.44%; new bone formed from coagulum: 53.02%; β-TCP + DBB:33.47%). Conclusions: Endo-sinus bone gained after OSFE inevitably and significantly shrinks regardless of whether grafting material is applied or not. Grafting material offers no significant advantage to stability nor clinical success of hydrophilic and nanostructured implants placed simultaneously with OSFE.
	\|}		\|}

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-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/PMC4418341  Ann Am Thorac Soc. 2015 May;12(5):648-56. PMID: PMC4418341 ] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4418341/ PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/25719895  Ann Am Thorac Soc. 2015 May;12(5):648-56. PMID: 25719895 ] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4418341 PDF]
 '''Authors:''' Jaramillo JD, Wilson C, Stinson DS, Lynch DA, Bowler RP, Lutz S, Bon JM, Arnold B, McDonald ML, Washko GR, Wan ES, DeMeo DL, Foreman MG, Soler X, Lindsay SE, Lane NE, Genant HK, Silverman EK, Hokanson JE, Make BJ, Crapo JD, Regan EA; COPDGene Investigators.

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 '''Background/Purpose:''' Computed tomography (CT) is the standard imaging modality in radiation therapy treatment planning (RTP). However, magnetic resonance (MR) imaging provides superior soft tissue contrast, increasing the precision of target volume selection. We present MR-only based RTP for a rat brain on a small animal radiation research platform (SARRP) using probabilistic voxel classification with multiple MR sequences. Six rat heads were imaged, each with one CT and five MR sequences. The MR sequences were: T1-weighted, T2-weighted, zero-echo time (ZTE), and two ultra-short echo time sequences with 20 μs (UTE1) and 2 ms (UTE2) echo times. CT data were manually segmented into air, soft tissue, and bone to obtain the RTP reference. Bias field corrected MR images were automatically segmented into the same tissue classes using a fuzzy c-means segmentation algorithm with multiple images as input. Similarities between segmented CT and automatic segmented MR (ASMR) images were evaluated using Dice coefficient. Three ASMR images with high similarity index were used for further RTP. Three beam arrangements were investigated. Dose distributions were compared by analysing dose volume histograms. The highest Dice coefficients were obtained for the ZTE-UTE2 combination and for the T1-UTE1-T2 combination when ZTE was unavailable. Both combinations, along with UTE1-UTE2, often used to generate ASMR images, were used for further RTP. Using 1 beam, MR based RTP underestimated the dose to be delivered to the target (range: 1.4%-7.6%). When more complex beam configurations were used, the calculated dose using the ZTE-UTE2 combination was the most accurate, with 0.7% deviation from CT, compared to 0.8% for T1-UTE1-T2 and 1.7% for UTE1-UTE2. The presented MR-only based workflow for RTP on a SARRP enables both accurate organ delineation and dose calculations using multiple MR sequences. This method can be useful in longitudinal studies where CT's cumulative radiation dose might contribute to the total dose.
-|align="right"|[[image:Gutierrez-pone2015-fig2.jpg|thumb|300px| Illustration of a CB-CT and five MR images of the same animal.<br>
+|align="right"| [[image:Gutierrez-pone2015-fig2.jpg|thumb|300px| Illustration of a CB-CT and five MR images of the same animal.<br>
 a) Coronal CB-CT image and (b)-(f) biased field corrected and masked coronal MR images using a T1-weighted (b), T2-weighted (c), ZTE (d), UTE1 (e) and UTE2 (f) sequence.
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+|
-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26091254 Sci Rep. 2015 Jun 19;5:10950. PMID: 26091254]| [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4473644/pdf/srep10950.pdf  PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26091254 Sci Rep. 2015 Jun 19;5:10950. PMID: 26091254] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4473644/pdf/srep10950.pdf  PDF]
 '''Authors:''' Sadagopan S, Temiz-Karayol NZ, Voss HU.
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-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26186462 PLoS One. 2015 Jul 17;10(7):e0132887. PMID: 26186462]| [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4505854/pdf/pone.0132887.pdf PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26186462 PLoS One. 2015 Jul 17;10(7):e0132887. PMID: 26186462] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4505854/pdf/pone.0132887.pdf PDF]
 '''Authors:''' Colombo MC, Giverso C, Faggiano E, Boffano C, Acerbi F, Ciarletta P
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-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=25069602 Int J Med Robot. 2015 Jun;11(2):256-67. PMID: 25069602]| [http://onlinelibrary.wiley.com/doi/10.1002/rcs.1602/pdf PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=25069602 Int J Med Robot. 2015 Jun;11(2):256-67. PMID: 25069602] | [http://onlinelibrary.wiley.com/doi/10.1002/rcs.1602/pdf PDF]
 '''Authors:''' Liu WP, Reaugamornrat S, Sorger JM, Siewerdsen JH, Taylor RH, Richmon JD.
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+|
-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/25824618 Neurobiol Aging. 2015 Jun;36(6):2122-9. PMID: 25824618]| [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433616/pdf/nihms671513.pdf PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/25824618 Neurobiol Aging. 2015 Jun;36(6):2122-9. PMID: 25824618] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4433616/pdf/nihms671513.pdf PDF]
 '''Authors:''' Cavallari M, Hshieh TT, Guttmann CR, Ngo LH, Meier DS, Schmitt EM, Marcantonio ER, Jones RN, Kosar CM, Fong TG, Press D, Inouye SK, Alsop DC, SAGES Study Group.
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+|
-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26236073 Proc SPIE Int Soc Opt Eng. 2015 Mar 17;9417.  PMID: 26236073]| [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4518713/pdf/nihms697978.pdf PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26236073 Proc SPIE Int Soc Opt Eng. 2015 Mar 17;9417.  PMID: 26236073] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4518713/pdf/nihms697978.pdf PDF]
 '''Authors:''' Paniagua B, Pera J, Budin F, Gomes L, Styner M, Lucia C, Nguyen T.
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+|
-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26085710 Proc SPIE Int Soc Opt Eng. 2015 Mar 17;9417. PMID: 26085710]| [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4466905/pdf/nihms697974.pdf PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26085710 Proc SPIE Int Soc Opt Eng. 2015 Mar 17;9417. PMID: 26085710] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4466905/pdf/nihms697974.pdf PDF]
 '''Authors:''' Paniagua B, Ruellas AC, Benavides E, Marron S, Woldford L, Cevidanes L.

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-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26112975 Biomed Eng Online. 2015 Jun 26;14:62. PMID: 26112975]| [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482101/pdf/12938_2015_Article_60.pdf| PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26112975 Biomed Eng Online. 2015 Jun 26;14:62. PMID: 26112975] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4482101/pdf/12938_2015_Article_60.pdf| PDF]
 '''Authors:''' Nardelli P, Khan KA, Corvò A, Moore N, Murphy MJ, Twomey M, O'Connor OJ, Kennedy MP, Estépar RS, Maher MM, Cantillon-Murphy P.

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-'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26241802 PLoS Biol. 2015 Aug 4;13(8):e1002212.  PMID: 26241802]| [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4524611/pdf/pbio.1002212.pdf PDF]
+'''Publication:''' [http://www.ncbi.nlm.nih.gov/pubmed/?term=26241802 PLoS Biol. 2015 Aug 4;13(8):e1002212.  PMID: 26241802] | [http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4524611/pdf/pbio.1002212.pdf PDF]
 '''Authors:''' Stern T, Aviram R, Rot C, Galili T, Sharir A, Kalish Achrai N, Keller Y, Shahar R, Zelzer E.