Abstract：
:Highly relevant for both clinical and legal medicine applications, the established radiological methods for estimating unknown age in children and adolescents are based on visual examination of bone ossification in X-ray images of the hand. Our group has initiated the development of fully automatic age estimation methods from 3D MRI scans of the hand, in order to simultaneously overcome the problems of the radiological methods including (1) exposure to ionizing radiation, (2) necessity to define new, MRI specific staging systems, and (3) subjective influence of the examiner. The present work provides a theoretical background for understanding the nonlinear regression problem of biological age estimation and chronological age approximation. Based on this theoretical background, we comprehensively evaluate machine learning methods (random forests, deep convolutional neural networks) with different simplifications of the image information used as an input for learning. Trained on a large dataset of 328 MR images, we compare the performance of the different input strategies and demonstrate unprecedented results. For estimating biological age, we obtain a mean absolute error of 0.37 ± 0.51 years for the age range of the subjects ≤ 18 years, i.e. where bone ossification has not yet saturated. Finally, we validate our findings by adapting our best performing method to 2D images and applying it to a publicly available dataset of X-ray images, showing that we are in line with the state-of-the-art automatic methods for this task.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Štern D,Payer C,Urschler Mdoi
10.1016/j.media.2019.101538subject
Has Abstractpub_date
2019-12-01 00:00:00pages
101538eissn
1361-8415issn
1361-8423pii
S1361-8415(18)30479-1journal_volume
58pub_type
杂志文章abstract：:Both resting state fMRI (R-fMRI) and task-based fMRI (T-fMRI) have been widely used to study the functional activities of the human brain during task-free and task-performance periods, respectively. However, due to the difficulty in strictly controlling the participating subject's mental status and their cognitive beh...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.07.003
更新日期：2013-12-01 00:00:00
abstract：:Quantitative magnetic resonance imaging (qMRI) is a technique for estimating quantitative tissue properties, such as the T1 and T2 relaxation times, apparent diffusion coefficient (ADC), and various perfusion measures. This estimation is achieved by acquiring multiple images with different acquisition parameters (or a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.12.004
更新日期：2016-04-01 00:00:00
abstract：:After two decades of increasing interest and research activity, computer-assisted diagnostic approaches are reaching the stage where more routine deployment in clinical practice is becoming a possibility [Kruppinski, E.A., 2004. Computer-aided detection in clinical environment: Benefits and challenges for radiologists...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2005.06.003
更新日期：2006-04-01 00:00:00
abstract：:We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2006.05.007
更新日期：2006-08-01 00:00:00
abstract：:In this work, we first propose an original and efficient computational framework to model continuous diffusion MRI (dMRI) signals and analytically recover important diffusion features such as the Ensemble Average Propagator (EAP) and the Orientation Distribution Function (ODF). Then, we develop an efficient parametric...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.04.011
更新日期：2013-10-01 00:00:00
abstract：:In this paper an automatic atlas-based segmentation algorithm for 4D cardiac MR images is proposed. The algorithm is based on the 4D extension of the expectation maximisation (EM) algorithm. The EM algorithm uses a 4D probabilistic cardiac atlas to estimate the initial model parameters and to integrate a priori inform...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2004.06.005
更新日期：2004-09-01 00:00:00
abstract：:A novel method for estimating a field of fiber orientation distribution (FOD) based on signal de-convolution from a given set of diffusion weighted magnetic resonance (DW-MR) images is presented. We model the FOD by higher order Cartesian tensor basis using a parametrization that explicitly enforces the positive semi-...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2012.07.002
更新日期：2012-08-01 00:00:00
abstract：:Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the early stage using longitudinal data, with each task corresponding to a pa...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.01.007
更新日期：2019-04-01 00:00:00
abstract：:Clinical acceptance of 3-D OCT retinal imaging brought rapid development of quantitative 3-D analysis of retinal layers, vasculature, retinal lesions as well as facilitated new research in retinal diseases. One of the cornerstones of many such analyses is segmentation and thickness quantification of retinal layers and...
journal_title：Medical image analysis
pub_type： 社论
doi：10.1016/j.media.2016.06.001
更新日期：2016-10-01 00:00:00
abstract：:Registration of three-dimensional ultrasound (3DUS) volumes is necessary in several applications, such as when stitching volumes to expand the field of view or when stabilizing a temporal sequence of volumes to cancel out motion of the probe or anatomy. Current systems that register 3DUS volumes either use external tr...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.10.004
更新日期：2012-02-01 00:00:00
abstract：:The accurate localization of anatomical landmarks is a challenging task, often solved by domain specific approaches. We propose a method for the automatic localization of landmarks in complex, repetitive anatomical structures. The key idea is to combine three steps: (1) a classifier for pre-filtering anatomical landma...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2013.02.004
更新日期：2013-12-01 00:00:00
abstract：:Interpretation of ultrasound videos of the fetal heart is crucial for the antenatal diagnosis of congenital heart disease (CHD). We believe that automated image analysis techniques could make an important contribution towards improving CHD detection rates. However, to our knowledge, no previous work has been done in t...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.11.006
更新日期：2017-02-01 00:00:00
abstract：:Statistical shape models (SSMs) have by now been firmly established as a robust tool for segmentation of medical images. While 2D models have been in use since the early 1990 s, wide-spread utilization of three-dimensional models appeared only in recent years, primarily made possible by breakthroughs in automatic dete...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2009.05.004
更新日期：2009-08-01 00:00:00
abstract：:In this work, various wavelet based methods like the discrete wavelet transform, the dual-tree complex wavelet transform, the Gabor wavelet transform, curvelets, contourlets and shearlets are applied for the automated classification of colonic polyps. The methods are tested on 8 HD-endoscopic image databases, where ea...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2016.02.001
更新日期：2016-07-01 00:00:00
abstract：:In this paper, we propose a novel automated pipeline for extraction of sulcal fundi from triangulated cortical surfaces. This method consists of four consecutive steps. Firstly, we adopt a finite difference method to estimate principal curvatures, principal directions and curvature derivatives, along the principal dir...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2010.01.005
更新日期：2010-06-01 00:00:00
abstract：:We describe a new algorithm for non-rigid registration capable of estimating a constrained dense displacement field from multi-modal image data. We applied this algorithm to capture non-rigid deformation between digital images of histological slides and digital flat-bed scanned images of cryotomed sections of the lary...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2005.04.003
更新日期：2005-12-01 00:00:00
abstract：:Human brain alignment based on imaging data has long been an intriguing research topic. One of the challenges is the huge inter-individual variabilities, which are pronounced not only in cortical folding patterns, but also in the underlying structural and functional patterns. Also, it is still not fully understood how...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101700
更新日期：2020-07-01 00:00:00
abstract：:The spinal cord is an essential and vulnerable component of the central nervous system. Differentiating and localizing the spinal cord internal structure (i.e., gray matter vs. white matter) is critical for assessment of therapeutic impacts and determining prognosis of relevant conditions. Fortunately, new magnetic re...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.01.003
更新日期：2014-04-01 00:00:00
abstract：:Current neuroimaging investigation of the white matter typically focuses on measurements derived from diffusion tensor imaging, such as fractional anisotropy (FA). In contrast, imaging studies of the gray matter oftentimes focus on morphological features such as cortical thickness, folding and surface curvature. As a ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2014.06.013
更新日期：2014-12-01 00:00:00
abstract：:Lung CAD systems require the ability to classify a variety of pulmonary structures as part of the diagnostic process. The purpose of this work was to develop a methodology for fully automated voxel-by-voxel classification of airways, fissures, nodules, and vessels from chest CT images using a single feature set and cl...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2007.03.004
更新日期：2007-06-01 00:00:00
abstract：:Atlas-based methods for automated preoperative planning of the femoral stem implant in total hip arthroplasty are described. Statistical atlases are constructed from a number of past preoperative plans prepared by experienced surgeons in order to represent the surgeon's expertise of the planning. Two types of atlases ...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.10.005
更新日期：2012-02-01 00:00:00
abstract：:This paper describes a new robust and fully automatic method for calibration of three-dimensional (3D) freehand ultrasound called Confhusius (CalibratiON for FreeHand UltraSound Imaging USage). 3D Freehand ultrasound consists in mounting a position sensor on a standard probe. The echographic B-scans can be localized i...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2004.06.021
更新日期：2005-02-01 00:00:00
abstract：:A stochastic finite element framework is presented for the simultaneous estimation of the cardiac kinematic functions and material model parameters from periodic medical image sequences. While existing biomechanics studies of the myocardial material constitutive laws have assumed known tissue kinematic measurements, a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/s1361-8415(03)00066-5
更新日期：2003-12-01 00:00:00
abstract：:The problem of respiratory motion has proved a serious obstacle in developing techniques to acquire images or guide interventions in abdominal and thoracic organs. Motion models offer a possible solution to these problems, and as a result the field of respiratory motion modelling has become an active one over the past...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2012.09.005
更新日期：2013-01-01 00:00:00
abstract：:Cortical thickness estimation in magnetic resonance imaging (MRI) is an important technique for research on brain development and neurodegenerative diseases. This paper presents a heat kernel based cortical thickness estimation algorithm, which is driven by the graph spectrum and the heat kernel theory, to capture the...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2015.01.005
更新日期：2015-05-01 00:00:00
abstract：:Segmentation of abdominal organs has been a comprehensive, yet unresolved, research field for many years. In the last decade, intensive developments in deep learning (DL) introduced new state-of-the-art segmentation systems. Despite outperforming the overall accuracy of existing systems, the effects of DL model proper...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2020.101950
更新日期：2020-12-25 00:00:00
abstract：:This paper presents a robust algorithm for calibration and system registration of endoscopic imaging devices. The system registration allows us to map accurately each point in the world coordinate system into the endoscope image and vice versa to obtain the world line of sight for each image pixel. The key point of ou...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2007.04.006
更新日期：2007-12-01 00:00:00
abstract：:The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. However, due to the large scale of WSIs and various sizes of the abnormal area, how to select informative regions and analyze them are quite challenging during the automatic diagnosis process. The multi-instance learning bas...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2019.101549
更新日期：2019-12-01 00:00:00
abstract：:The eye affords a unique opportunity to inspect a rich part of the human microvasculature non-invasively via retinal imaging. Retinal blood vessel segmentation and classification are prime steps for the diagnosis and risk assessment of microvascular and systemic diseases. A high volume of techniques based on deep lear...
journal_title：Medical image analysis
pub_type： 杂志文章,评审
doi：10.1016/j.media.2020.101905
更新日期：2021-02-01 00:00:00
abstract：:In this work we propose a comprehensive study of Digital Stent Enhancement (DSE), from the analysis of the requirements to the validation of the proposed solution. First, we derive the stent visualization requirements in the context of the clinical application and workflow. Then, we propose a DSE algorithm combining a...
journal_title：Medical image analysis
pub_type： 杂志文章
doi：10.1016/j.media.2011.03.002
更新日期：2011-08-01 00:00:00
