Multi-scale label interaction to improve object detection and segmentation

The project aims at advancing the state of the art in the use of context information for classification of image and video data. The use of context in the classification of images has been showed of great importance to improve the performance of actual object recognition systems. In our project we proposed the concept of Multi-scale Feature Labels as a general and compact method to exploit the local and global context. The feature extraction from the discriminative probability or classification confidence label field is of great novelty. Moreover the use of a multi-scale representation of the feature labels lead to a compact and efficient description of the context. The goal of the project has been also to provide a general-purpose method and prove its suitability in different image/video analysis problem. The two-year project generated 5 journal publications (plus 2 under submission), 10 conference publications (plus 2 under submission) and one patent (plus 1 pending). Of these publications, a relevant number make use of the main result of this project to improve the results in detection and/or segmentation of objects.

Atlas-based segmentation of pathological brain MR images

We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.

Development of a Manual Crack Quantification and Automated Crack Measurment System, Project TR-457 Final Report, 2005

Final report produced by DOT on development of manual crack quantification and automatic crack measurment system.

Three-dimensional morphological analysis of intracranial aneurysms: a fully automated method for aneurysm sac isolation and quantification

Morphological descriptors are practical and essential biomarkers for diagnosis andtreatment selection for intracranial aneurysm management according to the current guidelinesin use. Nevertheless, relatively little work has been dedicated to improve the three-dimensionalquanti cation of aneurysmal morphology, automate the analysis, and hence reduce the inherentintra- and inter-observer variability of manual analysis. In this paper we propose a methodologyfor the automated isolation and morphological quanti cation of saccular intracranial aneurysmsbased on a 3D representation of the vascular anatomy.

Simultaneous detection of aneuploidies for chromosomes 4, 6, 10 and 17 by automated four colour I-FISH in high hyperdiploid acute lymphoblastic leukemia : diagnostic assessment, clonal heterogeneity and chromosomal instability in adults

SummarySimultaneous detection of aneuploidies for chromosomes 4, 6,10 and 17 by automated four color l-FISH in high hyperdiploid acute lymphoblastic leukemia: diagnostic assessment, clonal heterogeneity and chromosomal instability in adultsAnna Talamo BlandinService de Génétique Médicale, Unité de Cytogénétique du Cancer, CHUVAcute lymphoblastic leukemia (ALL) is a malignant hemopathy characterized by the accumulation of the immature lymphoid cells in the bone marrow and, most often, in the peripheral blood. ALL is a heterogeneous disease with distinct biological and prognostic entities. At diagnosis, cytogenetic and molecular findings constitute important and independent prognostic factors. High hyperdiploidy with 51-67 chromosomes (HeH), one of the largest cytogenetic subsets of ALL, in childhood particularly, is generally associated with a relatively favorable outcome. Chromosome gain is nonrandom, extracopies of some chromosome occurring more frequently than those of others. Concurrent presence of trisomy for chromosomes 4, 10 and 17 confers an especially good prognosis. The first aim of our work was to develop an automated four color interphase fluorescence in situ hybridization (l-FISH) methodology and to assess its ability to detect concurrent aneuploidies 4, 6, 10 and 17 in 10 ALL patients. Various combinations of aneuploidies were identified. All clones detected by conventional cytogenetics were also observed by l-FISH. However, in all patients, l-FISH revealed numerous additional abnormal clones, leading to a high level of clonal heterogeneity. Our second aim has been to investigate the nature and origin of this clonal heterogeneity and to test for the presence of chromosome instability (CIN) in HeH ALL at initial presentation. Ten HeH ALL and 10 non-HeH ALL patients were analysed by four colour l-FISH and numerical CIN values were determined for all four chromosomes together and for each chromosome and patient group, an original approach in ALL. CIN values in HeH ALL proved to be much higher than#iose in non-HeH ALL, suggesting that numerical CIN may be at the origin of the high level of clonal heterogeneity revealed by l-FISH. Our third aim has been to study the evolution of these cytogenetic features during the course of the disease in 10 HeH ALL patients. Clonal heterogeneity was also observed again during disease progression, particularly at relapse. Clones detected at initial presentation generally reappeared in relapse, in most cases with newly generated ones. A significant correlation between the number of abnormal clones and CIN suggested that the higher the instability, the larger the number of abnormal clones. Whereas clonal heterogeneity and its evolution most probably result from underlying chromosome instability, operating processes remain conjectural.RésuméLa leucémie lymphoblastique aiguë (LLA) est une hémopathie maligne qui résulte de l'accumulationde cellules lymphoïdes immatures dans la moelle osseuse, et, le plus souvent, dans le sangpériphérique également. La LLA est une affection hétérogène au sein de laquelle se distinguentplusieurs entités biologiques et pronostiques. Les données cytogénétiques et moléculaires font partieintégrante du diagnostic et jouent un rôle essentiel dans l'évaluation du pronostic. L'hyperdiploïdieélevée à 51-­67 chromosomes (HeH), relativement fréquente, en particulier chez l'enfant, s'associe àun pronostic favorable. Le gain de chromosomes ne relève pas du hasard, certains chromosomesétant plus fréquemment impliqués que d'autres. La présence simultanée des trisomies 4, 6, et 17s'associe à un pronostic particulièrement bon. Le premier but du travail a été de développer uneméthode d'analyse automatique par hybridation in situ fluorescente interphasique (I-­FISH) à 4couleurs et de tester sa capacité à identifier la présence simultanée d'aneuploïdies 4, 6, 10 et 17 dans10 cas de LLA. Différentes combinaisons d'aneuploïdies ont été identifiées. Tous les clones détectéspar cytogénétique conventionnelle l'ont été par I-­FISH. Or, chez tous les patients, l'I-­FISH a révélé denombreux clones anormaux additionnels générant un degré élevé d'hétérogénéité clonale. Notredeuxième but a été d'investiguer la nature et l'origine de cette hétérogénéité et de tester la présenced'instabilité chromosomique (CIN) chez les patients avec une LLA HeH en presentation initiale. DixLLA HeH et 10 LLA non-­HeH ont été analysées par I-­FISH et les valeurs de CIN numérique ont étédéterminées pour les 4 chromosomes ensemble et pour chaque chromosome et groupe de patients,approche originale dans la LLA. Ces valeurs étant beaucoup plus élevées dans la LLA HeH que dansla LLA non-­HeH, elles favorisent l'hypothèse selon laquelle la CIN serait à l'origine de l'hétérogénéitéclonale révélée par I-­FISH. Le troisième but de notre travail a été d'étudier l'évolution de cescaractéristiques cytogénétiques au cours de la maladie dans 10 cas de LLA HeH. L'hétérogénéitéclonale a été retrouvée lors de la progression de la maladie, en particulier en rechute, où les clonesanormaux détectés en présentation initiale réapparaissent, généralement accompagnés de clonesnouveaux. La corrélation existant entre nombre de clones anormaux et valeurs de CIN suggère queplus l'instabilité est élevée, plus le nombre de clones anormaux est grand. Bien que l'hétérogénéitéclonale et son évolution résultent très probablement de l'instabilité chromosomique, les processus àl'oeuvre ne sont pas entièrement élucidés.

Examining the Agreement of Structural Loss Measured With Heidelberg Retinal Tomograhy and Functional Loss With Standard Automated Perimetry (SAP; Octopus), Pulsar Perimetry (PP), and Moorfields Motion Displacement Test (MDT) Perimetry

Purpose: To examine the relationship of functional measurements with structural measures. Methods: 146 eyes of 83 test subjects underwent Heidelberg Retinal Tomography (HRTIII) (disc area<2.43, mphsd<40), and perimetry testing with Octopus (SAP; Dynamic), Pulsar (PP; TOP) and Moorfields MDT (ESTA). Glaucoma was defined as progressive structural or functional loss (20 eyes). Perimetry test points were grouped into 6 sectors based on the estimated optic nerve head angle into which the associated nerve fiber bundle enters (Garway-Heath map). Perimetry summary measures (PSM) (MD SAP/ MD PP/ PTD MDT) were calculated from the average total deviation of each measured threshold from the normal for each sector. We calculated the 95% significance level of the sectorial PSM from the respective normative data. We calculated the percentage agreement with group1 (G1), healthy on HRT and within normal perimetric limits, and group 2 (G2), abnormal on HRT and outside normal perimetric limits. We also examined the relationship of PSM and rim area (RA) in those sectors classified as abnormal by MRA (Moorfields Regression Analysis) of HRT. Results: The mean age was 65 (range= [37, 89]). The global sensitivity versus specificity of each instrument in detecting glaucomatous eyes was: MDT 80% vs. 88%, SAP 80% vs. 80%, PP 70% vs. 89% and HRT 80% vs. 79%. Highest percentage agreement of HRT (respectively G1, G2, sector) with PSM were MDT (89%, 57%, nasal superior), SAP (83%, 74%, temporal superior), PP (74%, 63%, nasal superior). Globally percentage agreement (respectively G1, G2) was MDT (92%, 28%), SAP (87%, 40%) and PP (77%, 49%). Linear regression showed there was no significant trend globally associating RA and PSM. However, sectorally the supero-nasal sector had a statistically significant (p<0.001) trend with each instrument, the associated r2 coefficients are (MDT 0.38 SAP 0.56 and PP 0.39). Conclusions: There were no significant differences in global sensitivity or specificity between instruments. Structure-function relationships varied significantly between instruments and were consistently strongest supero-nasally. Further studies are required to investigate these relationships in detail.

MP2RAGE, a self bias-field corrected sequence for improved segmentation and T1-mapping at high field.

The large spatial inhomogeneity in transmit B(1) field (B(1)(+)) observable in human MR images at high static magnetic fields (B(0)) severely impairs image quality. To overcome this effect in brain T(1)-weighted images, the MPRAGE sequence was modified to generate two different images at different inversion times, MP2RAGE. By combining the two images in a novel fashion, it was possible to create T(1)-weighted images where the result image was free of proton density contrast, T(2) contrast, reception bias field, and, to first order, transmit field inhomogeneity. MP2RAGE sequence parameters were optimized using Bloch equations to maximize contrast-to-noise ratio per unit of time between brain tissues and minimize the effect of B(1)(+) variations through space. Images of high anatomical quality and excellent brain tissue differentiation suitable for applications such as segmentation and voxel-based morphometry were obtained at 3 and 7 T. From such T(1)-weighted images, acquired within 12 min, high-resolution 3D T(1) maps were routinely calculated at 7 T with sub-millimeter voxel resolution (0.65-0.85 mm isotropic). T(1) maps were validated in phantom experiments. In humans, the T(1) values obtained at 7 T were 1.15+/-0.06 s for white matter (WM) and 1.92+/-0.16 s for grey matter (GM), in good agreement with literature values obtained at lower spatial resolution. At 3 T, where whole-brain acquisitions with 1 mm isotropic voxels were acquired in 8 min, the T(1) values obtained (0.81+/-0.03 s for WM and 1.35+/-0.05 for GM) were once again found to be in very good agreement with values in the literature.

Automated auditory mismatch negativity paradigm improves coma prognostic accuracy after cardiac arrest and therapeutic hypothermia.

PURPOSE: EEG and somatosensory evoked potential are highly predictive of poor outcome after cardiac arrest; their accuracy for good recovery is however low. We evaluated whether addition of an automated mismatch negativity-based auditory discrimination paradigm (ADP) to EEG and somatosensory evoked potential improves prediction of awakening. METHODS: EEG and ADP were prospectively recorded in 30 adults during therapeutic hypothermia and in normothermia. We studied the progression of auditory discrimination on single-trial multivariate analyses from therapeutic hypothermia to normothermia, and its correlation to outcome at 3 months, assessed with cerebral performance categories. RESULTS: At 3 months, 18 of 30 patients (60%) survived; 5 had severe neurologic impairment (cerebral performance categories = 3) and 13 had good recovery (cerebral performance categories = 1-2). All 10 subjects showing improvements of auditory discrimination from therapeutic hypothermia to normothermia regained consciousness: ADP was 100% predictive for awakening. The addition of ADP significantly improved mortality prediction (area under the curve, 0.77 for standard model including clinical examination, EEG, somatosensory evoked potential, versus 0.86 after adding ADP, P = 0.02). CONCLUSIONS: This automated ADP significantly improves early coma prognostic accuracy after cardiac arrest and therapeutic hypothermia. The progression of auditory discrimination is strongly predictive of favorable recovery and appears complementary to existing prognosticators of poor outcome. Before routine implementation, validation on larger cohorts is warranted.

Multiparametric brainstem segmentation using a modified multivariate mixture of Gaussians

The human brainstem is a densely packed, complex but highly organised structure. It not only serves as a conduit for long projecting axons conveying motor and sensory information, but also is the location of multiple primary nuclei that control or modulate a vast array of functions, including homeostasis, consciousness, locomotion, and reflexive and emotive behaviours. Despite its importance, both in understanding normal brain function as well as neurodegenerative processes, it remains a sparsely studied structure in the neuroimaging literature. In part, this is due to the difficulties in imaging the internal architecture of the brainstem in vivo in a reliable and repeatable fashion. A modified multivariate mixture of Gaussians (mmMoG) was applied to the problem of multichannel tissue segmentation. By using quantitative magnetisation transfer and proton density maps acquired at 3 T with 0.8 mm isotropic resolution, tissue probability maps for four distinct tissue classes within the human brainstem were created. These were compared against an ex vivo fixated human brain, imaged at 0.5 mm, with excellent anatomical correspondence. These probability maps were used within SPM8 to create accurate individual subject segmentations, which were then used for further quantitative analysis. As an example, brainstem asymmetries were assessed across 34 right-handed individuals using voxel based morphometry (VBM) and tensor based morphometry (TBM), demonstrating highly significant differences within localised regions that corresponded to motor and vocalisation networks. This method may have important implications for future research into MRI biomarkers of pre-clinical neurodegenerative diseases such as Parkinson's disease.

Liver segmentation: Practical tips.

The liver segmentation system, described by Couinaud, is based on the identification of the three hepatic veins and the plane passing by the portal vein bifurcation. Nowadays, Couinaud's description is the most widely used classification since it is better suited for surgery and more accurate for the localisation and monitoring of intra-parenchymal lesions. Knowledge of the anatomy of the portal and venous system is therefore essential, as is knowledge of the variants resulting from changes occurring during the embryological development of the vitelline and umbilical veins. In this paper, the authors propose a straightforward systematisation of the liver in six steps using several additional anatomical points of reference. These points of reference are simple and quickly identifiable in any radiological examination with section imaging, in order to avoid any mistakes in daily practice. In fact, accurate description impacts on many diagnostic and therapeutic applications in interventional radiology and surgery. This description will allow better preparation for biopsy, portal vein embolisation, transjugular intrahepatic portosystemic shunt, tumour resection or partial hepatectomy for transplantation. Such advance planning will reduce intra- and postoperative difficulties and complications.

Automated quantitative pupillometry for the prognostication of coma after cardiac arrest.

BACKGROUND: Sedation and therapeutic hypothermia (TH) delay neurological responses and might reduce the accuracy of clinical examination to predict outcome after cardiac arrest (CA). We examined the accuracy of quantitative pupillary light reactivity (PLR), using an automated infrared pupillometry, to predict outcome of post-CA coma in comparison to standard PLR, EEG, and somato-sensory evoked potentials (SSEP). METHODS: We prospectively studied over a 1-year period (June 2012-June 2013) 50 consecutive comatose CA patients treated with TH (33 °C, 24 h). Quantitative PLR (expressed as the % of pupillary response to a calibrated light stimulus) and standard PLR were measured at day 1 (TH and sedation; on average 16 h after CA) and day 2 (normothermia, off sedation: on average 46 h after CA). Neurological outcome was assessed at 90 days with Cerebral Performance Categories (CPC), dichotomized as good (CPC 1-2) versus poor (CPC 3-5). Predictive performance was analyzed using area under the ROC curves (AUC). RESULTS: Patients with good outcome [n = 23 (46 %)] had higher quantitative PLR than those with poor outcome [n = 27; 16 (range 9-23) vs. 10 (1-30) % at day 1, and 20 (13-39) vs. 11 (1-55) % at day 2, both p < 0.001]. Best cut-off for outcome prediction of quantitative PLR was <13 %. The AUC to predict poor outcome was higher for quantitative than for standard PLR at both time points (day 1, 0.79 vs. 0.56, p = 0.005; day 2, 0.81 vs. 0.64, p = 0.006). Prognostic accuracy of quantitative PLR was comparable to that of EEG and SSEP (0.81 vs. 0.80 and 0.73, respectively, both p > 0.20). CONCLUSIONS: Quantitative PLR is more accurate than standard PLR in predicting outcome of post-anoxic coma, irrespective of temperature and sedation, and has comparable prognostic accuracy than EEG and SSEP.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.