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Author |
Debora Gil; Antonio Esteban Lansaque; Sebastian Stefaniga; Mihail Gaianu; Carles Sanchez |
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Title |
Data Augmentation from Sketch |
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Conference Article |
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Year |
2019 |
Publication |
International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging |
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11840 |
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155-162 |
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Keywords |
Data augmentation; cycleGANs; Multi-objective optimization |
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Abstract |
State of the art machine learning methods need huge amounts of data with unambiguous annotations for their training. In the context of medical imaging this is, in general, a very difficult task due to limited access to clinical data, the time required for manual annotations and variability across experts. Simulated data could serve for data augmentation provided that its appearance was comparable to the actual appearance of intra-operative acquisitions. Generative Adversarial Networks (GANs) are a powerful tool for artistic style transfer, but lack a criteria for selecting epochs ensuring also preservation of intra-operative content.
We propose a multi-objective optimization strategy for a selection of cycleGAN epochs ensuring a mapping between virtual images and the intra-operative domain preserving anatomical content. Our approach has been applied to simulate intra-operative bronchoscopic videos and chest CT scans from virtual sketches generated using simple graphical primitives. |
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Shenzhen; China; October 2019 |
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IAM; 600.145; 601.337; 600.139; 600.145 |
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Admin @ si @ GES2019 |
Serial |
3359 |
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Author |
Santi Puch; Irina Sanchez; Aura Hernandez-Sabate; Gemma Piella; Vesna Prckovska |
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Title |
Global Planar Convolutions for Improved Context Aggregation in Brain Tumor Segmentation |
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Conference Article |
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Year |
2018 |
Publication |
International MICCAI Brainlesion Workshop |
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11384 |
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393-405 |
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Brain tumors; 3D fully-convolutional CNN; Magnetic resonance imaging; Global planar convolution |
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In this work, we introduce the Global Planar Convolution module as a building-block for fully-convolutional networks that aggregates global information and, therefore, enhances the context perception capabilities of segmentation networks in the context of brain tumor segmentation. We implement two baseline architectures (3D UNet and a residual version of 3D UNet, ResUNet) and present a novel architecture based on these two architectures, ContextNet, that includes the proposed Global Planar Convolution module. We show that the addition of such module eliminates the need of building networks with several representation levels, which tend to be over-parametrized and to showcase slow rates of convergence. Furthermore, we provide a visual demonstration of the behavior of GPC modules via visualization of intermediate representations. We finally participate in the 2018 edition of the BraTS challenge with our best performing models, that are based on ContextNet, and report the evaluation scores on the validation and the test sets of the challenge. |
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MICCAIW |
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ADAS; 600.118;IAM |
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Admin @ si @ PSH2018 |
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3251 |
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Author |
Esmitt Ramirez; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil |
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Title |
Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy |
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Conference Article |
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Year |
2018 |
Publication |
OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis |
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11041 |
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Biopsy guiding; Bronchoscopy; Lung biopsy; Intervention guiding; Airway codification |
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Bronchoscopy examinations allow biopsy of pulmonary nodules with minimum risk for the patient. Even for experienced bronchoscopists, it is difficult to guide the bronchoscope to most distal lesions and obtain an accurate diagnosis. This paper presents an image-based codification of the bronchial anatomy for bronchoscopy biopsy guiding. The 3D anatomy of each patient is codified as a binary tree with nodes representing bronchial levels and edges labeled using their position on images projecting the 3D anatomy from a set of branching points. The paths from the root to leaves provide a codification of navigation routes with spatially consistent labels according to the anatomy observes in video bronchoscopy explorations. We evaluate our labeling approach as a guiding system in terms of the number of bronchial levels correctly codified, also in the number of labels-based instructions correctly supplied, using generalized mixed models and computer-generated data. Results obtained for three independent observers prove the consistency and reproducibility of our guiding system. We trust that our codification based on viewer’s projection might be used as a foundation for the navigation process in Virtual Bronchoscopy systems. |
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Granada; September 2018 |
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MICCAIW |
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IAM; 600.096; 600.075; 601.323; 600.145 |
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Call Number |
Admin @ si @ RSB2018b |
Serial |
3137 |
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Author |
Debora Gil; Oriol Ramos Terrades; Elisa Minchole; Carles Sanchez; Noelia Cubero de Frutos; Marta Diez-Ferrer; Rosa Maria Ortiz; Antoni Rosell |
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Title |
Classification of Confocal Endomicroscopy Patterns for Diagnosis of Lung Cancer |
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Conference Article |
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Year |
2017 |
Publication |
6th Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging |
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10550 |
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151-159 |
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Confocal Laser Endomicroscopy (CLE) is an emerging imaging technique that allows the in-vivo acquisition of cell patterns of potentially malignant lesions. Such patterns could discriminate between inflammatory and neoplastic lesions and, thus, serve as a first in-vivo biopsy to discard cases that do not actually require a cell biopsy.
The goal of this work is to explore whether CLE images obtained during videobronchoscopy contain enough visual information to discriminate between benign and malign peripheral lesions for lung cancer diagnosis. To do so, we have performed a pilot comparative study with 12 patients (6 adenocarcinoma and 6 benign-inflammatory) using 2 different methods for CLE pattern analysis: visual analysis by 3 experts and a novel methodology that uses graph methods to find patterns in pre-trained feature spaces. Our preliminary results indicate that although visual analysis can only achieve a 60.2% of accuracy, the accuracy of the proposed unsupervised image pattern classification raises to 84.6%.
We conclude that CLE images visual information allow in-vivo detection of neoplastic lesions and graph structural analysis applied to deep-learning feature spaces can achieve competitive results. |
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Quebec; Canada; September 2017 |
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Notes |
IAM; 600.096; 600.075; 600.145;DAG |
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Call Number |
Admin @ si @ GRM2017 |
Serial |
2957 |
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Author |
Antoni Gurgui; Debora Gil; Enric Marti; Vicente Grau |
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Title |
Left-Ventricle Basal Region Constrained Parametric Mapping to Unitary Domain |
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Conference Article |
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Year |
2016 |
Publication |
7th International Workshop on Statistical Atlases & Computational Modelling of the Heart |
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Volume |
10124 |
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163-171 |
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Keywords |
Laplacian; Constrained maps; Parameterization; Basal ring |
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Due to its complex geometry, the basal ring is often omitted when putting different heart geometries into correspondence. In this paper, we present the first results on a new mapping of the left ventricle basal rings onto a normalized coordinate system using a fold-over free approach to the solution to the Laplacian. To guarantee correspondences between different basal rings, we imposed some internal constrained positions at anatomical landmarks in the normalized coordinate system. To prevent internal fold-overs, constraints are handled by cutting the volume into regions defined by anatomical features and mapping each piece of the volume separately. Initial results presented in this paper indicate that our method is able to handle internal constrains without introducing fold-overs and thus guarantees one-to-one mappings between different basal ring geometries. |
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Athens; October 2016 |
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STACOM |
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IAM; |
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Admin @ si @ GGM2016 |
Serial |
2884 |
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Author |
Aura Hernandez-Sabate; Lluis Albarracin; Daniel Calvo; Nuria Gorgorio |
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Title |
EyeMath: Identifying Mathematics Problem Solving Processes in a RTS Video Game |
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Conference Article |
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Year |
2016 |
Publication |
5th International Conference Games and Learning Alliance |
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10056 |
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50-59 |
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Keywords |
Simulation environment; Automated Driving; Driver-Vehicle interaction |
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Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical. |
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GALA |
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ADAS;IAM; |
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HAC2016 |
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2864 |
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Author |
Saad Minhas; Aura Hernandez-Sabate; Shoaib Ehsan; Katerine Diaz; Ales Leonardis; Antonio Lopez; Klaus McDonald Maier |
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Title |
LEE: A photorealistic Virtual Environment for Assessing Driver-Vehicle Interactions in Self-Driving Mode |
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Conference Article |
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2016 |
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14th European Conference on Computer Vision Workshops |
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9915 |
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894-900 |
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Keywords |
Simulation environment; Automated Driving; Driver-Vehicle interaction |
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Abstract |
Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical. |
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Amsterdam; The Netherlands; October 2016 |
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ECCVW |
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ADAS;IAM; 600.085; 600.076 |
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MHE2016 |
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2865 |
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Carles Sanchez; Debora Gil; Jorge Bernal; F. Javier Sanchez; Marta Diez-Ferrer; Antoni Rosell |
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Title |
Navigation Path Retrieval from Videobronchoscopy using Bronchial Branches |
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Conference Article |
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2016 |
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19th International Conference on Medical Image Computing and Computer Assisted Intervention Workshops |
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9401 |
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62-70 |
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Bronchoscopy navigation; Lumen center; Brochial branches; Navigation path; Videobronchoscopy |
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Abstract |
Bronchoscopy biopsy can be used to diagnose lung cancer without risking complications of other interventions like transthoracic needle aspiration. During bronchoscopy, the clinician has to navigate through the bronchial tree to the target lesion. A main drawback is the difficulty to check whether the exploration is following the correct path. The usual guidance using fluoroscopy implies repeated radiation of the clinician, while alternative systems (like electromagnetic navigation) require specific equipment that increases intervention costs. We propose to compute the navigated path using anatomical landmarks extracted from the sole analysis of videobronchoscopy images. Such landmarks allow matching the current exploration to the path previously planned on a CT to indicate clinician whether the planning is being correctly followed or not. We present a feasibility study of our landmark based CT-video matching using bronchoscopic videos simulated on a virtual bronchoscopy interactive interface. |
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Quebec; Canada; September 2016 |
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MICCAIW |
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IAM; MV; 600.060; 600.075 |
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Admin @ si @ SGB2016 |
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2885 |
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Author |
Sergio Vera; Debora Gil; Miguel Angel Gonzalez Ballester |
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Anatomical parameterization for volumetric meshing of the liver |
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Conference Article |
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2014 |
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SPIE – Medical Imaging |
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9036 |
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Coordinate System; Anatomy Modeling; Parameterization |
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A coordinate system describing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specific anatomical landmarks, the coordinate system allows integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric coordinate systems over the surface of anatomical shapes, given their flexibility to set values
at specific locations through boundary conditions. However, most of the existing implementations in medical imaging restrict to either anatomical surfaces, or the depth coordinate with boundary conditions is given at sites
of limited geometric diversity. In this paper we present a method for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the
volume medial surface. We have applied the methodology to define a common reference system for the liver shape and functional anatomy. This reference system sets a solid base for creating anatomical models of the patient’s liver, and allows comparing livers from several patients in a common framework of reference. |
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Amsterdam; September 2014 |
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SPIE-MI |
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IAM; 600.075 |
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Admin @ si @ VGG2014 |
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2456 |
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Author |
Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez |
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Title |
Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis |
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Conference Article |
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2014 |
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1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy |
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8899 |
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1-10 |
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Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps |
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In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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LNCS |
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0302-9743 |
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978-3-319-13409-3 |
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CARE |
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MV; IAM; 600.044; 600.047; 600.060; 600.075 |
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Admin @ si @ BGS2014b |
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2503 |
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