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Abnormal optic disc and retinal vessels in children with surgically treated hydrocephalus.

https://arctichealth.org/en/permalink/ahliterature90653
Source
Br J Ophthalmol. 2009 Apr;93(4):526-30
Publication Type
Article
Date
Apr-2009
Author
Andersson S.
Hellström A.
Author Affiliation
Department of Ophthalmology, The Queen Silvia Children's Hospital, Sahlgrenska University Hospital/Ostra, 416 85 Göteborg, Sweden. susann.andersson@oft.gu.se
Source
Br J Ophthalmol. 2009 Apr;93(4):526-30
Date
Apr-2009
Language
English
Publication Type
Article
Keywords
Adolescent
Child
Child, Preschool
Female
Fundus Oculi
Gestational Age
Humans
Hydrocephalus - complications - epidemiology - pathology - surgery
Image Processing, Computer-Assisted - methods
Infant, Newborn
Male
Ophthalmoscopy
Optic Atrophy - epidemiology - etiology - pathology
Prospective Studies
Retinal Vessels - pathology
Sweden - epidemiology
Young Adult
Abstract
AIMS: To investigate the morphology of the optic disc and retinal vessels in children with surgically treated hydrocephalus. METHODS: A prospective, population-based study was performed in 69 children (median age 9.6 years) with early surgically treated hydrocephalus. All children were examined by ophthalmoscopy. Additionally, optic disc and retinal vessel morphology was evaluated in 55 children by digital image analysis of ocular fundus photographs. RESULTS: Optic atrophy was found in 10 of 69 children (14%). In comparison with a reference group, the median optic-disc area was significantly smaller (p = 0.013) in the children with hydrocephalus. There was no corresponding difference in cup area, so the rim area was significantly smaller in the hydrocephalic children (p = 0.002). Children with hydrocephalus had an abnormal retinal vascular pattern, with significantly straighter retinal arteries and fewer central vessel branching points compared with controls (p
PubMed ID
19106149 View in PubMed
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Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk.

https://arctichealth.org/en/permalink/ahliterature300458
Source
Breast Cancer Res. 2018 12 29; 20(1):156
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Date
12-29-2018
Author
Sue Hudson
Kirsti Vik Hjerkind
Sarah Vinnicombe
Steve Allen
Cassia Trewin
Giske Ursin
Isabel Dos-Santos-Silva
Bianca L De Stavola
Author Affiliation
Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK. susan.hudson@lshtm.ac.uk.
Source
Breast Cancer Res. 2018 12 29; 20(1):156
Date
12-29-2018
Language
English
Publication Type
Journal Article
Research Support, Non-U.S. Gov't
Keywords
Adiposity
Aged
Aged, 80 and over
Body mass index
Breast - diagnostic imaging - pathology
Breast Density
Breast Neoplasms - diagnostic imaging - pathology
Case-Control Studies
Cohort Studies
Feasibility Studies
Female
Humans
Image Processing, Computer-Assisted - methods
Logistic Models
Mammography - methods
Mass Screening - methods
Middle Aged
Norway
Risk assessment
Risk factors
United Kingdom
Abstract
Fully automated assessment of mammographic density (MD), a biomarker of breast cancer risk, is being increasingly performed in screening settings. However, data on body mass index (BMI), a confounder of the MD-risk association, are not routinely collected at screening. We investigated whether the amount of fat in the breast, as captured by the amount of mammographic non-dense tissue seen on the mammographic image, can be used as a proxy for BMI when data on the latter are unavailable.
Data from a UK case control study (numbers of cases/controls: 414/685) and a Norwegian cohort study (numbers of cases/non-cases: 657/61059), both with volumetric MD measurements (dense volume (DV), non-dense volume (NDV) and percent density (%MD)) from screening-age women, were analysed. BMI (self-reported) and NDV were taken as measures of adiposity. Correlations between BMI and NDV, %MD and DV were examined after log-transformation and adjustment for age, menopausal status and parity. Logistic regression models were fitted to the UK study, and Cox regression models to the Norwegian study, to assess associations between MD and breast cancer risk, expressed as odds/hazard ratios per adjusted standard deviation (OPERA). Adjustments were first made for standard risk factors except BMI (minimally adjusted models) and then also for BMI or NDV. OPERA pooled relative risks (RRs) were estimated by fixed-effect models, and between-study heterogeneity was assessed by the I2 statistics.
BMI was positively correlated with NDV (adjusted r = 0.74 in the UK study and r = 0.72 in the Norwegian study) and with DV (r = 0.33 and r = 0.25, respectively). Both %MD and DV were positively associated with breast cancer risk in minimally adjusted models (pooled OPERA RR (95% confidence interval): 1.34 (1.25, 1.43) and 1.46 (1.36, 1.56), respectively; I2 = 0%, P >0.48 for both). Further adjustment for BMI or NDV strengthened the %MD-risk association (1.51 (1.41, 1.61); I2 = 0%, P = 0.33 and 1.51 (1.41, 1.61); I2 = 0%, P = 0.32, respectively). Adjusting for BMI or NDV marginally affected the magnitude of the DV-risk association (1.44 (1.34, 1.54); I2 = 0%, P = 0.87 and 1.49 (1.40, 1.60); I2 = 0%, P = 0.36, respectively).
When volumetric MD-breast cancer risk associations are investigated, NDV can be used as a measure of adiposity when BMI data are unavailable.
PubMed ID
30594212 View in PubMed
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The AGES-Reykjavik study atlases: Non-linear multi-spectral template and atlases for studies of the ageing brain.

https://arctichealth.org/en/permalink/ahliterature292006
Source
Med Image Anal. 2017 Jul; 39:133-144
Publication Type
Journal Article
Date
Jul-2017
Author
Lars Forsberg
Sigurdur Sigurdsson
Jesper Fredriksson
Asdis Egilsdottir
Bryndis Oskarsdottir
Olafur Kjartansson
Mark A van Buchem
Lenore J Launer
Vilmundur Gudnason
Alex Zijdenbos
Author Affiliation
The Icelandic Heart Association, Kopavogur, Iceland; Department of Neuroscience, Karolinska Institutet, Stockholm, Sweden. Electronic address: larsef@me.com.
Source
Med Image Anal. 2017 Jul; 39:133-144
Date
Jul-2017
Language
English
Publication Type
Journal Article
Keywords
Aged
Aging
Algorithms
Anatomy, Artistic
Atlases as Topic
Brain - diagnostic imaging
Female
Humans
Image Processing, Computer-Assisted - methods
Magnetic Resonance Imaging - methods
Male
Abstract
Quantitative analyses of brain structures from Magnetic Resonance (MR) image data are often performed using automatic segmentation algorithms. Many of these algorithms rely on templates and atlases in a common coordinate space. Most freely available brain atlases are generated from relatively young individuals and not always derived from well-defined cohort studies. In this paper, we introduce a publicly available multi-spectral template with corresponding tissue probability atlases and regional atlases, optimised to use in studies of ageing cohorts (mean age 75 ± 5 years). Furthermore, we provide validation data from a regional segmentation pipeline to assure the integrity of the dataset.
Notes
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PubMed ID
28501699 View in PubMed
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Agreement between image grading of conventional (45°) and ultra wide-angle (200°) digital images in the macula in the Reykjavik eye study.

https://arctichealth.org/en/permalink/ahliterature143099
Source
Eye (Lond). 2010 Oct;24(10):1568-75
Publication Type
Article
Date
Oct-2010
Author
A. Csutak
I. Lengyel
F. Jonasson
I. Leung
A. Geirsdottir
W. Xing
T. Peto
Author Affiliation
Moorfields Eye Hospital, London, England.
Source
Eye (Lond). 2010 Oct;24(10):1568-75
Date
Oct-2010
Language
English
Publication Type
Article
Keywords
Diagnostic Imaging - methods
Feasibility Studies
Follow-Up Studies
Humans
Image Processing, Computer-Assisted - methods
Macula Lutea - pathology
Macular Degeneration - diagnosis
Abstract
To establish the agreement between image grading of conventional (45°) and ultra wide-angle (200°) digital images in the macula.
In 2008, the 12-year follow-up was conducted on 573 participants of the Reykjavik Eye Study. This study included the use of the Optos P200C AF ultra wide-angle laser scanning ophthalmoscope alongside Zeiss FF 450 conventional digital fundus camera on 121 eyes with or without age-related macular degeneration using the International Classification System. Of these eyes, detailed grading was carried out on five cases each with hard drusen, geographic atrophy and chorioretinal neovascularisation, and six cases of soft drusen. Exact agreement and ?-statistics were calculated.
Comparison of the conventional and ultra wide-angle images in the macula showed an overall 96.43% agreement (?=0.93) with no disagreement at end-stage disease; although in one eye chorioretinal neovascularisation was graded as drusenoid pigment epithelial detachment. Of patients with drusen only, the exact agreement was 96.1%. The detailed grading showed no clinically significant disagreement between the conventional 45° and 200° images.
On the basis of our results, there is a good agreement between grading conventional and ultra wide-angle images in the macula.
PubMed ID
20523357 View in PubMed
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Automated image analysis of cyclin D1 protein expression in invasive lobular breast carcinoma provides independent prognostic information.

https://arctichealth.org/en/permalink/ahliterature123920
Source
Hum Pathol. 2012 Nov;43(11):2053-61
Publication Type
Article
Date
Nov-2012
Author
Nicholas P Tobin
Katja L Lundgren
Catherine Conway
Lola Anagnostaki
Sean Costello
Göran Landberg
Author Affiliation
Breakthrough Breast Cancer Research Unit, School of Cancer, Enabling Sciences and Technology, University of Manchester, Manchester Academic Health Science Centre, Paterson Institute for Cancer Research, The Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX, UK.
Source
Hum Pathol. 2012 Nov;43(11):2053-61
Date
Nov-2012
Language
English
Publication Type
Article
Keywords
Adult
Aged
Aged, 80 and over
Algorithms
Breast Neoplasms - diagnosis - metabolism - mortality
Carcinoma, Lobular - diagnosis - metabolism - mortality
Cell Nucleus - metabolism - pathology
Cyclin D1 - metabolism
Disease-Free Survival
Female
Gene Amplification
Humans
Image Processing, Computer-Assisted - methods
Mastectomy
Middle Aged
Neoplasm Invasiveness
Neoplasm Staging
Prognosis
Survival Rate
Sweden - epidemiology
Tumor Markers, Biological - metabolism
Abstract
The emergence of automated image analysis algorithms has aided the enumeration, quantification, and immunohistochemical analyses of tumor cells in both whole section and tissue microarray samples. To date, the focus of such algorithms in the breast cancer setting has been on traditional markers in the common invasive ductal carcinoma subtype. Here, we aimed to optimize and validate an automated analysis of the cell cycle regulator cyclin D1 in a large collection of invasive lobular carcinoma and relate its expression to clinicopathologic data. The image analysis algorithm was trained to optimally match manual scoring of cyclin D1 protein expression in a subset of invasive lobular carcinoma tissue microarray cores. The algorithm was capable of distinguishing cyclin D1-positive cells and illustrated high correlation with traditional manual scoring (?=0.63). It was then applied to our entire cohort of 483 patients, with subsequent statistical comparisons to clinical data. We found no correlation between cyclin D1 expression and tumor size, grade, and lymph node status. However, overexpression of the protein was associated with reduced recurrence-free survival (P=.029), as was positive nodal status (P
PubMed ID
22647349 View in PubMed
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Automated image analysis of proliferating cells in carcinoma of the larynx.

https://arctichealth.org/en/permalink/ahliterature18220
Source
Acta Otolaryngol. 2003 Aug;123(6):759-66
Publication Type
Article
Date
Aug-2003
Author
Jaakko Laitakari
David Harrison
Frej Stenbäck
Author Affiliation
Department of Pathology, University of Oulu, Oulu, Finland.
Source
Acta Otolaryngol. 2003 Aug;123(6):759-66
Date
Aug-2003
Language
English
Publication Type
Article
Keywords
Carcinoma, Squamous Cell - immunology - pathology - physiopathology
Cell Division - physiology
Cell Transformation, Neoplastic
Humans
Image Processing, Computer-Assisted - methods
Laryngeal Mucosa - immunology - pathology
Laryngeal Neoplasms - immunology - pathology - physiopathology
Nuclear Proteins - diagnostic use - immunology
Precancerous Conditions - immunology - pathology - physiopathology
Proliferating Cell Nuclear Antigen - diagnostic use - immunology
Research Support, Non-U.S. Gov't
Retrospective Studies
Abstract
OBJECTIVE: To determine the role of cell proliferation neoplastic progression in the larynx and possibly derive criteria of clinical significance using automated quantitative image analysis. MATERIAL AND METHODS: In a retrospective study involving archival material, the occurrence and location, size, shape and staining intensity of proliferating cell nuclear antigen (PCNA)-positive cells (12,538 cells in total) were analyzed in squamous cell carcinoma (SCC), as well as in pre- and non-neoplastic conditions, using computer-assisted morphometry with reproducibility and sensitivity exceeding 99%. RESULTS: Immunohistochemically detectable PCNA-positive cells were located in the basal layer in non-neoplastic states, in well-differentiated SCCs in layers adjacent to the basal membrane and in poorly differentiated neoplasms in the neoplastic epithelial islets. An increased degree of dysplasia was associated with an increased number of PCNA-immunoreactive cells of increased nuclear size and staining intensity. There was a significant difference between carcinomas and dysplasia in terms of altered nuclear shape. With increasing malignancy of SCCs, nuclear shape alterations and PCNA staining intensity increased, whilst nuclear size decreased. CONCLUSIONS: Automated image analysis of cell populations allowed the identification of populations of malignant cells and provided information on the severity of preneoplastic and neoplastic conditions of use in studies of tumor behavior and with potential clinical application.
PubMed ID
12953780 View in PubMed
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Automatic segmentation and recognition of lungs and lesion from CT scans of thorax.

https://arctichealth.org/en/permalink/ahliterature90938
Source
Comput Med Imaging Graph. 2009 Jan;33(1):72-82
Publication Type
Article
Date
Jan-2009
Author
Kakar Manish
Olsen Dag Rune
Author Affiliation
Department of Radiation Biology, Institute for Cancer Research, Rikshospitalet-Radiumhospitalet Medical centre, Oslo, Norway. Manish.Kakar@rr-research.no
Source
Comput Med Imaging Graph. 2009 Jan;33(1):72-82
Date
Jan-2009
Language
English
Publication Type
Article
Keywords
Anatomy, Cross-Sectional - methods
Cluster analysis
Fuzzy Logic
Humans
Image Processing, Computer-Assisted - methods
Imaging, Three-Dimensional - methods
Lung - pathology - radiography
Lung Neoplasms - pathology - radiography
Models, Statistical
Neural Networks (Computer)
Norway
Pattern Recognition, Automated - methods
Radiography, Thoracic - methods
Sensitivity and specificity
Thorax - pathology
Tomography, X-Ray Computed - methods
Abstract
In this study, a fully automated texture-based segmentation and recognition system for lesion and lungs from CT of thorax is presented. For the segmentation part, we have extracted texture features by Gabor filtering the images, and, then combined these features to segment the target volume by using Fuzzy C Means (FCM) clustering. Since clustering is sensitive to initialization of cluster prototypes, optimal initialization of the cluster prototypes was done by using a Genetic Algorithm. For the recognition stage, we have used cortex like mechanism for extracting statistical features in addition to shape-based features. The segmented regions showed a high degree of imbalance between positive and negative samples, so we employed over and under sampling for balancing the data. Finally, the balanced and normalized data was subjected to Support Vector Machine (SimpleSVM) for training and testing. Results reveal an accuracy of delineation to be 94.06%, 94.32% and 89.04% for left lung, right lung and lesion, respectively. Average sensitivity of the SVM classifier was seen to be 89.48%.
PubMed ID
19059759 View in PubMed
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Comparing image processing techniques for improved 3-dimensional ultrasound imaging.

https://arctichealth.org/en/permalink/ahliterature97442
Source
J Ultrasound Med. 2010 Apr;29(4):615-9
Publication Type
Article
Date
Apr-2010
Author
Flemming Forsberg
Vincenzo Berghella
Daniel A Merton
Keith Rychlak
Joann Meiers
Barry B Goldberg
Author Affiliation
Department of Radiology, Division of Ultrasound, Thomas Jefferson University, Philadelphia, PA 19107, USA. flemming.forsberg@jefferson.edu
Source
J Ultrasound Med. 2010 Apr;29(4):615-9
Date
Apr-2010
Language
English
Publication Type
Article
Keywords
Abdomen - ultrasonography
Adult
Female
Humans
Image Enhancement - methods
Image Processing, Computer-Assisted - methods
Imaging, Three-Dimensional - methods
Male
Pregnancy
Prospective Studies
Software
Statistics, nonparametric
Ultrasonography, Prenatal - methods
Abstract
OBJECTIVE: The purpose of this study was to compare volumetric image processing techniques for reducing noise and speckle while retaining tissue structures in 3-dimensional (3D) gray scale ultrasound imaging. METHODS: Eighty subjects underwent a clinically indicated abdominal or obstetric 3D ultrasound examination (20 hepatic, 20 renal, and 40 obstetric cases). Volume data were processed on a pixel ("2-dimensional [2D] processing") or a voxel ("3D processing") basis using commercially available image enhancement software (ContextVision AB, Linköping, Sweden). Randomized, side-by-side comparisons of the image processing techniques were performed for each subject. An independent and blinded reader scored the volumes for image quality on a 3-point scale from 1 (worst) to 3 (best) and compared the results using a nonparametric Wilcoxson signed rank test. RESULTS: The 40 subjects with abdominal 3D imaging received a mean score (+/- 1 SD) of 1.52 +/- 0.51, 2.45 +/- 0.60, and 2.75 +/- 0.44 for the original, the 2D processed, and the 3D processed volumes, respectively. The differences between the unprocessed and the processed volumes were highly statistically significant (P
PubMed ID
20375380 View in PubMed
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Comparison of methods for detecting nondeterministic BOLD fluctuation in fMRI.

https://arctichealth.org/en/permalink/ahliterature30465
Source
Magn Reson Imaging. 2004 Feb;22(2):197-203
Publication Type
Article
Date
Feb-2004
Author
Vesa Kiviniemi
Juha-Heikki Kantola
Jukka Jauhiainen
Osmo Tervonen
Author Affiliation
Department of Diagnostic Radiology, University of Oulu, Oys, Finland. vkivinie@mail.student.oulu.fi
Source
Magn Reson Imaging. 2004 Feb;22(2):197-203
Date
Feb-2004
Language
English
Publication Type
Article
Keywords
Anesthesia
Brain Mapping
Cerebral Arteries - anatomy & histology
Cerebral Cortex - blood supply
Cerebrovascular Circulation
Child
Child, Preschool
Comparative Study
Fourier Analysis
Humans
Image Processing, Computer-Assisted - methods
Magnetic Resonance Imaging - methods
Oxygen - blood
Signal Processing, Computer-Assisted
Visual Cortex - blood supply
Abstract
Functional MR imaging (fMRI) has been used in detecting neuronal activation and intrinsic blood flow fluctuations in the brain cortex. This article is aimed for comparing the methods for analyzing the nondeterministic flow fluctuations. Fast Fourier Transformation (FFT), cross correlation (CC), spatial principal component analysis (sPCA), and independent component analysis (sICA) were compared. 15 subjects were imaged at 1.5 T. Three quantitative measures were compared: (1) The number of subjects with identifiable fluctuation, (2) the volume, and (3) mean correlation coefficient (MCC) of the detected voxels. The focusing on cortical structures and the overall usability were qualitatively assessed. sICA was spatially most accurate but time consuming, robust, and detected voxels with high temporal synchrony. The CC and FFT were fast suiting primary screening. The CC detected highest temporal synchrony but the subjective detection for reference vector produced excess variance of the detected volumes. The FFT and sPCA were not spatially accurate and did not detect adequate temporal synchrony of the voxels.
PubMed ID
15010111 View in PubMed
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Computer-assisted diagnosis by temporal subtraction in postoperative brain tumor patients: a feasibility study.

https://arctichealth.org/en/permalink/ahliterature17575
Source
Acad Radiol. 2004 Aug;11(8):887-93
Publication Type
Article
Date
Aug-2004
Author
Eero Ilkko
Kari Suomi
Ari Karttunen
Osmo Tervonen
Author Affiliation
Department of Diagnostic Radiology, Oulu University Hospital, PL 50, 90029 OYS, Finland. eero.ilkko@ppshp.fi
Source
Acad Radiol. 2004 Aug;11(8):887-93
Date
Aug-2004
Language
English
Publication Type
Article
Keywords
Adolescent
Adult
Aged
Astrocytoma - pathology - surgery
Brain - pathology
Brain Neoplasms - pathology - surgery
Color
Comparative Study
Contrast Media
Diagnosis, Computer-Assisted
Feasibility Studies
Female
Gadolinium DTPA - diagnostic use
Glioma - pathology - surgery
Hemangiopericytoma - pathology - surgery
Humans
Image Enhancement - methods
Image Processing, Computer-Assisted - methods
Magnetic Resonance Imaging - methods
Male
Middle Aged
Subtraction Technique
Abstract
RATIONALE AND OBJECTIVES: To introduce and evaluate a novel, image fusion-based technique that can be used to compare the findings of primary and control brain magnetic resonance imaging scans, with special attention to the differences found in this comparison. MATERIALS AND METHODS: A new technique named "colored difference mapping" was applied to the brain examinations of five patients. The possible changes in the magnetic resonance imaging findings were analyzed by the colored difference mapping technique and by using conventional film reading and the results were compared. RESULTS: Colored difference mapping accurately depicts the differences between successive magnetic resonance images and reveals small changes that are difficult to perceive in a visual evaluation. CONCLUSION: Colored difference mapping is suitable for comparison of images between two different radiologic examinations and helps to show even minimal changes in brain tissues.
PubMed ID
15288039 View in PubMed
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41 records – page 1 of 5.