Automatic Quantitative Analysis of 3D Brain Data Sets: Application to a Pediatric Population

Spectrum-imaging is a useful technique for comparing different processing methods on very large data sets which are identical for each method. This paper is concerned with comparing methods of electron energy-loss spectroscopy (EELS) quantitative analysis on the Al-Li system. The spectrum-image analyzed here was obtained from an Al-10at%Li foil aged to produce δ' precipitates that can span the foil thickness. Two 1024 channel EELS spectra offset in energy by 1 eV were recorded and stored at each pixel in the 80x80 spectrum-image (25 Mbytes). An energy range of 39-89eV (20 channels/eV) are represented. During processing the spectra are either subtracted to create an artifact corrected difference spectrum, or the energy offset is numerically removed and the spectra are added to create a normal spectrum. The spectrum-images are processed into 2D floating-point images using methods and software described in [1].

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WHATEVER YOU WANT: INCONSISTENT RESULTS IS THE RULE, NOT THE EXCEPTION, IN THE STUDY OF PRIMATE BRAIN EVOLUTION

10.1101/454132 ◽

2018 ◽

Cited By ~ 1

Author(s):

Andreas Wartel ◽

Patrik Lindenfors ◽

Johan Lind

Keyword(s):

Body Size ◽

Brain Evolution ◽

Data Sets ◽

Data Set ◽

Scientific Rigor ◽

Explanatory Variables ◽

Primate Brain ◽

Residual Variation ◽

The Many ◽

Brain Data

AbstractPrimate brains differ in size and architecture. Hypotheses to explain this variation are numerous and many tests have been carried out. However, after body size has been accounted for there is little left to explain. The proposed explanatory variables for the residual variation are many and covary, both with each other and with body size. Further, the data sets used in analyses have been small, especially in light of the many proposed predictors. Here we report the complete list of models that results from exhaustively combining six commonly used predictors of brain and neocortex size. This provides an overview of how the output from standard statistical analyses changes when the inclusion of different predictors is altered. By using both the most commonly tested brain data set and a new, larger data set, we show that the choice of included variables fundamentally changes the conclusions as to what drives primate brain evolution. Our analyses thus reveal why studies have had troubles replicating earlier results and instead have come to such different conclusions. Although our results are somewhat disheartening, they highlight the importance of scientific rigor when trying to answer difficult questions. It is our position that there is currently no empirical justification to highlight any particular hypotheses, of those adaptive hypotheses we have examined here, as the main determinant of primate brain evolution.

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Hierarchical ordering with partial pairwise hierarchical relationships on the macaque brain data sets

PLoS ONE ◽

10.1371/journal.pone.0177373 ◽

2017 ◽

Vol 12 (5) ◽

pp. e0177373

Author(s):

Woosang Lim ◽

Jungsoo Lee ◽

Yongsub Lim ◽

Doo-Hwan Bae ◽

Haesun Park ◽

...

Keyword(s):

Data Sets ◽

Hierarchical Relationships ◽

Hierarchical Ordering ◽

Brain Data

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Automatic quantification of MS lesions in 3D MRI brain data sets: Validation of INSECT

Medical Image Computing and Computer-Assisted Intervention — MICCAI’98 - Lecture Notes in Computer Science ◽

10.1007/bfb0056229 ◽

1998 ◽

pp. 439-448 ◽

Cited By ~ 64

Author(s):

Alex Zijdenbos ◽

Reza Forghani ◽

Alan Evans

Keyword(s):

Data Sets ◽

3D Mri ◽

Automatic Quantification ◽

Mri Brain ◽

Brain Data

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Pipelines: Large Scale Automatic Analysis of 3D Brain Data Sets

NeuroImage ◽

10.1016/s1053-8119(18)31616-1 ◽

1998 ◽

Vol 7 (4) ◽

pp. S783 ◽

Cited By ~ 5

Author(s):

Alex P. Zijdenbos ◽

Alberto Jimenez ◽

Alan C. Evans

Keyword(s):

Large Scale ◽

Automatic Analysis ◽

Data Sets ◽

Brain Data

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Short-term mortality following surgical procedures for the diagnosis of pediatric brain tumors: outcome analysis in 5533 children from SEER, 2004–2011

Journal of Neurosurgery Pediatrics ◽

10.3171/2015.7.peds15224 ◽

2016 ◽

Vol 17 (3) ◽

pp. 289-297 ◽

Cited By ~ 14

Author(s):

Todd C. Hankinson ◽

Roy W. R. Dudley ◽

Michelle R. Torok ◽

Mohana Rao Patibandla ◽

Kathleen Dorris ◽

...

Keyword(s):

Pediatric Population ◽

Pediatric Brain Tumor ◽

Outcome Analysis ◽

Data Sets ◽

Short Term ◽

Neurosurgical Procedure ◽

Risk Of Death ◽

Short Term Mortality ◽

Seer Data ◽

Pediatric Brain

OBJECT Thirty-day mortality is increasingly a reference metric regarding surgical outcomes. Recent data estimate a 30-day mortality rate of 1.4−2.7% after craniotomy for tumors in children. No detailed analysis of short-term mortality following a diagnostic neurosurgical procedure (e.g., resection or tissue biopsy) for tumor in the US pediatric population has been conducted. METHODS The Surveillance, Epidemiology and End Results (SEER) data sets identified patients ≤ 21 years who underwent a diagnostic neurosurgical procedure for primary intracranial tumor from 2004 to 2011. One- and two-month mortality was estimated. Standard statistical methods estimated associations between independent variables and mortality. RESULTS A total of 5533 patients met criteria for inclusion. Death occurred within the calendar month of surgery in 64 patients (1.16%) and by the conclusion of the calendar month following surgery in 95 patients (1.72%). Within the first calendar month, patients < 1 year of age (n = 318) had a risk of death of 5.66%, while those from 1 to 21 years (n = 5215) had a risk of 0.88% (p < 0.0001). By the end of the calendar month following surgery, patients < 1 year (n = 318) had a risk of death of 7.23%, while those from 1 to 21 years (n = 5215) had a risk of 1.38% (p < 0.0001). Children < 1 year at diagnosis were more likely to harbor a high-grade lesion than older children (OR 1.9, 95% CI 1.5–2.4). CONCLUSIONS In the SEER data sets, the risk of death within 30 days of a diagnostic neurosurgical procedure for a primary pediatric brain tumor is between 1.16% and 1.72%, consistent with contemporary data from European populations. The risk of mortality in infants is considerably higher, between 5.66% and 7.23%, and they harbor more aggressive lesions.

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MEASUREMENT, VISUALIZATION AND QUANTITATIVE ANALYSIS OF COMPLETE THREE-DIMENSIONAL KINEMATICAL DATA SETS OF HUMAN AND CAT MIDDLE EAR

Middle Ear Mechanics in Research and Otology ◽

10.1142/9789812703019_0001 ◽

2004 ◽

Cited By ~ 16

Author(s):

W.F. DECRAEMER ◽

S.M. KHANNA

Keyword(s):

Quantitative Analysis ◽

Middle Ear ◽

Three Dimensional ◽

Data Sets ◽

Kinematical Data

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The BAL-Score Almost Perfectly Predicts Testicular Torsion in Children: A Two-Center Cohort Study

Frontiers in Pediatrics ◽

10.3389/fped.2020.601892 ◽

2020 ◽

Vol 8 ◽

Author(s):

Michaela Klinke ◽

Julia Elrod ◽

Carolin Stiel ◽

Tarik Ghadban ◽

Julia Wenskus ◽

...

Keyword(s):

Testicular Torsion ◽

Medical Center ◽

Pediatric Population ◽

Scoring Systems ◽

Acute Scrotum ◽

Data Sets ◽

Multicenter Studies ◽

Diagnostic Reliability ◽

Predictive Values ◽

Surgery Department

Introduction: Testicular torsion (TT) is a common emergency that warrants immediate exploration to prevent infertility or testicular loss. To improve diagnostic reliability, various scoring systems have been published. The aim of this study was to evaluate and validate different testicular torsion scores in a large cohort of children with acute scrotum.Methods: Retrospective analysis of all male children that were admitted for acute scrotum at the Pediatric Surgery Department of the Altonaer Kinderkrankenhaus and University medical Center Hamburg-Eppendorf from 01/2013 to 03/2019. Two testicular torsion scores (Boettcher Alert Score, Testicular Workup for Ischemia and Suspected Torsion Score) were applied to all data sets. Furthermore, an artificial intelligence (AI)-based score was developed and compared to the two current scores.Results: In total, 460 boys were included in the study. Of those, 48 (10.4%) had TT. Children with TT suffered most often from short duration of pain, nausea and vomiting, high riding testicle and absent cremasteric reflex. The BALS and the AI-based score had excellent predictive values and all patients with TT would have been detected.Conclusion: The BAL and the AI score show excellent predictive capabilities and may be used to identify all cases of TT in a pediatric population. The scores are easy to apply. As the BALS was slightly better, we advocate to use this score but to validate our findings in prospective multicenter studies.

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