Abstract:
:In this study, we propose a novel anomaly detection model targeting subtle brain lesions in multiparametric MRI. To compensate for the lack of annotated data adequately sampling the heterogeneity of such pathologies, we cast this problem as an outlier detection problem and introduce a novel configuration of unsupervised deep siamese networks to learn normal brain representations using a series of non-pathological brain scans. The proposed siamese network, composed of stacked convolutional autoencoders as subnetworks is designed to map patches extracted from healthy control scans only and centered at the same spatial localization to 'close' representations with respect to the chosen metric in a latent space. It is based on a novel loss function combining a similarity term and a regularization term compensating for the lack of dissimilar pairs. These latent representations are then fed into oc-SVM models at voxel-level to produce anomaly score maps. We evaluate the performance of our brain anomaly detection model to detect subtle epilepsy lesions in multiparametric (T1-weighted, FLAIR) MRI exams considered as normal (MRI-negative). Our detection model trained on 75 healthy subjects and validated on 21 epilepsy patients (with 18 MRI-negatives) achieves a maximum sensitivity of 61% on the MRI-negative lesions, identified among the 5 most suspicious detections on average. It is shown to outperform detection models based on the same architecture but with stacked convolutional or Wasserstein autoencoders as unsupervised feature extraction mechanisms.
journal_name
Med Image Analjournal_title
Medical image analysisauthors
Alaverdyan Z,Jung J,Bouet R,Lartizien Cdoi
10.1016/j.media.2019.101618subject
Has Abstractpub_date
2020-02-01 00:00:00pages
101618eissn
1361-8415issn
1361-8423pii
S1361-8415(19)30156-2journal_volume
60pub_type
杂志文章abstract::Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale representation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires ne...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101749
更新日期:2020-12-01 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 introduce a new approach to medical image analysis that combines deformable model methodologies with concepts from the field of artificial life. In particular, we propose "deformable organisms", autonomous agents whose task is the automatic segmentation, labeling, and quantitative analysis of anatomical structures ...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/s1361-8415(02)00083-x
更新日期:2002-09-01 00:00:00
abstract::We propose HookNet, a semantic segmentation model for histopathology whole-slide images, which combines context and details via multiple branches of encoder-decoder convolutional neural networks. Concentric patches at multiple resolutions with different fields of view, feed different branches of HookNet, and intermedi...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101890
更新日期:2021-02-01 00:00:00
abstract::Alzheimers disease (AD) is a complex neurodegenerative disease. Its early diagnosis and treatment have been a major concern of researchers. Currently, the multi-modality data representation learning of this disease is gradually becoming an emerging research field, attracting widespread attention. However, in practice,...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101953
更新日期:2021-01-01 00:00:00
abstract::Accurate vertebral body (VB) detection and segmentation are critical for spine disease identification and diagnosis. Existing automatic VB detection and segmentation methods may cause false-positive results to the background tissue or inaccurate results to the desirable VB. Because they usually cannot take both the gl...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101861
更新日期:2021-01-01 00:00:00
abstract::As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to the clinical diagnosis and treatment of NFS. However, existing clinica...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2016.10.009
更新日期:2017-02-01 00:00:00
abstract::Classification of digital pathology images is imperative in cancer diagnosis and prognosis. Recent advancements in deep learning and computer vision have greatly benefited the pathology workflow by developing automated solutions for classification tasks. However, the cost and time for acquiring high quality task-speci...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101859
更新日期:2021-01-01 00:00:00
abstract::Over the past 20 years, the field of medical image registration has significantly advanced from multi-modal image fusion to highly non-linear, deformable image registration for a wide range of medical applications and imaging modalities, involving the compensation and analysis of physiological organ motion or of tissu...
journal_title:Medical image analysis
pub_type: 社论
doi:10.1016/j.media.2016.06.031
更新日期:2016-10-01 00:00:00
abstract::Fine-featured elastograms may provide additional information of radiological interest in the context of in vivo elastography. Here a new image processing pipeline called ESP (Elastography Software Pipeline) is developed to create Magnetic Resonance Elastography (MRE) maps of viscoelastic parameters (complex modulus ma...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2016.05.012
更新日期:2017-01-01 00:00:00
abstract::Diffusion tensor imaging can provide the fundamental information required for viewing structural connectivity. However, robust and accurate acquisition and processing algorithms are needed to accurately map the nerve connectivity. In this paper, we present a novel algorithm for extracting and visualizing the fiber tra...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2003.12.001
更新日期:2004-06-01 00:00:00
abstract::Image-based parcellation of the brain often leads to multiple disconnected anatomical structures, which pose significant challenges for analyses of morphological shapes. Existing shape models, such as the widely used spherical harmonic (SPHARM) representation, assume topological invariance, so are unable to simultaneo...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2015.02.004
更新日期:2015-05-01 00:00:00
abstract::With the development of deep learning, its application in diagnosis of benign and malignant thyroid nodules has been widely concerned. However, it is difficult to obtain medical images, resulting in insufficient number of data, which contradicts the large amount of data required for acquiring effective deep learning d...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101819
更新日期:2021-01-01 00:00:00
abstract::The Insight Toolkit (ITK) initiative from the National Library of Medicine has provided a suite of state-of-the-art segmentation and registration algorithms ideally suited to volume visualization and analysis. A volume visualization application that effectively utilizes these algorithms provides many benefits: it allo...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2005.04.009
更新日期:2005-12-01 00:00:00
abstract::Dynamic-susceptibility-contrast (DSC) magnetic resonance imaging records signal changes on images when the injected contrast-agent particles pass through a human brain. The temporal signal changes on different brain tissues manifest distinct blood-supply patterns which are vital for the profound analysis of cerebral h...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2007.02.002
更新日期:2007-06-01 00:00:00
abstract::In this paper, we propose a novel continuum finite strain formulation of the equilibrium gap regularization for image registration. The equilibrium gap regularization essentially penalizes any deviation from the solution of a hyperelastic body in equilibrium with arbitrary loads prescribed at the boundary. It thus rep...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2018.07.007
更新日期:2018-12-01 00:00:00
abstract::We propose a novel Riemannian framework for statistical analysis of shapes that is able to account for the nonlinearity in shape variation. By adopting a physical perspective, we introduce a differential representation that puts the local geometric variability into focus. We model these differential coordinates as ele...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2017.09.004
更新日期:2018-01-01 00:00:00
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 meth...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2019.101538
更新日期:2019-12-01 00:00:00
abstract::Deep learning-based systems can achieve a diagnostic performance comparable to physicians in a variety of medical use cases including the diagnosis of diabetic retinopathy. To be useful in clinical practice, it is necessary to have well calibrated measures of the uncertainty with which these systems report their decis...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101724
更新日期:2020-08-01 00:00:00
abstract::Examinations of the spinal column with both, Magnetic Resonance (MR) imaging and Computed Tomography (CT), often require a precise three-dimensional positioning, angulation and labeling of the spinal disks and the vertebrae. A fully automatic and robust approach is a prerequisite for an automated scan alignment as wel...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2012.09.007
更新日期:2013-12-01 00:00:00
abstract::Vascular pressure differences are established risk markers for a number of cardiovascular diseases. Relative pressures are, however, often driven by turbulence-induced flow fluctuations, where conventional non-invasive methods may yield inaccurate results. Recently, we proposed a novel method for non-turbulent flows, ...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2019.101627
更新日期:2020-02-01 00:00:00
abstract::Images of the retina acquired using optical coherence tomography (OCT) often suffer from intensity inhomogeneity problems that degrade both the quality of the images and the performance of automated algorithms utilized to measure structural changes. This intensity variation has many causes, including off-axis acquisit...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2017.09.008
更新日期:2018-01-01 00:00:00
abstract::Automated ventricle volume estimation (AVVE) on cardiac magnetic resonance (CMR) images is very important for clinical cardiac disease diagnosis. However, current AVVE methods ignore the error correction for the estimated volume. This results in clinically intolerable ventricle volume estimation error and further lead...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2020.101723
更新日期:2020-08-01 00:00:00
abstract::The in vivo investigation of joint kinematics in normal and injured wrist requires the segmentation of carpal bones from 3D (CT) images, and their registration over time. The non-uniformity of bone tissue, ranging from dense cortical bone to textured spongy bone, the irregular shape of closely packed carpal bones, sma...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/s1361-8415(02)00065-8
更新日期:2003-03-01 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 availability of a large amount of annotated data is critical for many medical image analysis applications, in particular for those relying on deep learning methods which are known to be data-hungry. However, annotated medical data, especially multimodal data, is often scarce and costly to obtain. In this paper, we...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2019.101565
更新日期:2020-01-01 00:00:00
abstract::Many cardiac pathologies are reflected in abnormal myocardial deformation, accessible through magnetic resonance tagging (MRT). Interpretation of the MRT data is difficult, since the relation between pathology and deformation is not straightforward. Mathematical models of cardiac mechanics could be used to translate m...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2006.04.001
更新日期:2006-08-01 00:00:00
abstract::In this note we summarize the history of computer aided surgery in orthopaedics and traumatology from the end of the nineteenth century to currently observable future trends. We concentrate on the two major components of such systems, pre-operative planning and intra-operative execution. The evolution of the necessary...
journal_title:Medical image analysis
pub_type: 社论
doi:10.1016/j.media.2016.06.033
更新日期:2016-10-01 00:00:00
abstract::The current standard of care for glaucoma patients consists of functional assessment of vision via visual field (VF) testing, which is sensitive but subjective, time-consuming, and often unreliable. A new imaging technology, Fourier domain optical coherence tomography (OCT), is being introduced to assess the structura...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2011.05.012
更新日期:2012-01-01 00:00:00
abstract::Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-consuming and unreliable) which is currently the gold standard for AIS...
journal_title:Medical image analysis
pub_type: 杂志文章
doi:10.1016/j.media.2018.05.005
更新日期:2018-08-01 00:00:00