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Saad Minhas, Aura Hernandez-Sabate, Shoaib Ehsan, & Klaus McDonald Maier. (2022). "Effects of Non-Driving Related Tasks during Self-Driving mode " . IEEE Transactions on Intelligent Transportation Systems, 23(2), 1391–1399.
Abstract: Perception reaction time and mental workload have proven to be crucial in manual driving. Moreover, in highly automated cars, where most of the research is focusing on Level 4 Autonomous driving, take-over performance is also a key factor when taking road safety into account. This study aims to investigate how the immersion in non-driving related tasks affects the take-over performance of drivers in given scenarios. The paper also highlights the use of virtual simulators to gather efficient data that can be crucial in easing the transition between manual and autonomous driving scenarios. The use of Computer Aided Simulations is of absolute importance in this day and age since the automotive industry is rapidly moving towards Autonomous technology. An experiment comprising of 40 subjects was performed to examine the reaction times of driver and the influence of other variables in the success of take-over performance in highly automated driving under different circumstances within a highway virtual environment. The results reflect the relationship between reaction times under different scenarios that the drivers might face under the circumstances stated above as well as the importance of variables such as velocity in the success on regaining car control after automated driving. The implications of the results acquired are important for understanding the criteria needed for designing Human Machine Interfaces specifically aimed towards automated driving conditions. Understanding the need to keep drivers in the loop during automation, whilst allowing drivers to safely engage in other non-driving related tasks is an important research area which can be aided by the proposed study.
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Saad Minhas, Zeba Khanam, Shoaib Ehsan, Klaus McDonald Maier, & Aura Hernandez-Sabate. (2022). "Weather Classification by Utilizing Synthetic Data " . Sensors, 22(9), 3193.
Abstract: Weather prediction from real-world images can be termed a complex task when targeting classification using neural networks. Moreover, the number of images throughout the available datasets can contain a huge amount of variance when comparing locations with the weather those images are representing. In this article, the capabilities of a custom built driver simulator are explored specifically to simulate a wide range of weather conditions. Moreover, the performance of a new synthetic dataset generated by the above simulator is also assessed. The results indicate that the use of synthetic datasets in conjunction with real-world datasets can increase the training efficiency of the CNNs by as much as 74%. The article paves a way forward to tackle the persistent problem of bias in vision-based datasets.
Keywords: Weather classification; synthetic data; dataset; autonomous car; computer vision; advanced driver assistance systems; deep learning; intelligent transportation systems
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Sandra Pujades, Francesc Carreras, Manuel Ballester, Jaume Garcia, & Debora Gil. (2008). "A Normalized Parametric Domain for the Analysis of the Left Ventricular Function " In Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISAPP’08) (Vol. 1, pp. 267–274).
Abstract: Impairment of left ventricular (LV) contractility due to cardiovascular diseases is reflected in LV motion patterns. The mechanics of any muscle strongly depends on the spatial orientation of its muscular fibers since the motion that the muscle undergoes mainly takes place along the fiber. The helical ventricular myocardial band (HVMB) concept describes the myocardial muscle as a unique muscular band that twists in space in a non homogeneous fashion. The 3D anisotropy of the ventricular band fibers suggests a regional analysis of the heart motion. Computation of normality models of such motion can help in the detection and localization of any cardiac disorder. In this paper we introduce, for the first time, a normalized parametric domain that allows comparison of the left ventricle motion across patients. We address, both, extraction of the LV motion from Tagged Magnetic Resonance images, as well as, defining a mapping of the LV to a common normalized domain. Extraction of normality motion patterns from 17 healthy volunteers shows the clinical potential of our LV parametrization.
Keywords: Helical Ventricular Myocardial Band; Myocardial Fiber; Tagged Magnetic Resonance; HARP; Optical Flow Variational Framework; Gabor Filters; B-Splines.
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Sergio Vera. (2010). "Finger joint modelling from hand X-ray images for assessing rheumatoid arthritis " (Vol. 164). Master's thesis, , Bellaterra 01893, Barcelona, Spain.
Abstract: Rheumatoid arthritis is an autoimmune, systemic, inflammatory disorder that mainly af- fects bone joints. While there is no cure for this disease, continuous advances on palliative treatments require frequent verification of patient’s illness evolution. Such evolution is mea- sured through several available semi-quantitative methods that require evaluation of hand and foot X-ray images. Accurate assessment is a time consuming task that requires highly trained personnel. This hinders a generalized use in clinical practice for early diagnose and disease follow-up. In the context of the automatization of such evaluation methods we present a method for detection and characterization of finger joints in hand radiography images. Several measures for assessing the reduction of joint space width are proposed. We compare for the first time such measures to the Van der Heijde score, the gold standard method for rheumatoid arthritis assessment. The proposed method outperforms existing strategies with a detection rate above 95%. Our comparison to Van der Heijde index shows a promising correlation that encourages further research.
Keywords: Rheumatoid arthritis; joint detection; X-ray; Van der Heijde score
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Sergio Vera. (2015)." Anatomic Registration based on Medial Axis Parametrizations" (Debora Gil, & Miguel Angel Gonzalez Ballester, Eds.). Ph.D. thesis, Ediciones Graficas Rey, .
Abstract: Image registration has been for many years the gold standard method to bring two images into correspondence. It has been used extensively in the eld of medical imaging in order to put images of di erent patients into a common overlapping spatial position. However, medical image registration is a slow, iterative optimization process, where many variables and prone to fall into the pit traps local minima.
A coordinate system parameterizing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to speci c anatomical sites, parameterizations ensure integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric meshes over the surface of anatomical shapes, given their ability to set values at speci c 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 discrete sites of limited geometric diversity.
The medial surface of the shape can be used to provide a continuous basis for the de nition of a depth coordinate. However, given that di erent methods for generation of medial surfaces generate di erent manifolds, not all of them are equally suited to be the basis of radial coordinate for a parameterization. It would be desirable that the medial surface will be smooth, and robust to surface shape noise, with low number of spurious branches or surfaces.
In this thesis we present methods for computation of smooth medial manifolds and apply them to the generation of for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the volume medial surface. This reference system sets a solid base for creating anatomical models of the anatomical shapes, and allows comparing several patients in a common framework of reference.
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Sergio Vera, Debora Gil, Agnes Borras, F. Javier Sanchez, Frederic Perez, & Marius G. Linguraru. (2011)." Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs" In In H. Yoshida et al (Ed.), Workshop on Computational and Clinical Applications in Abdominal Imaging (Vol. 7029, pp. 223–230). Springer Berlin Heidelberg.
Abstract: Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
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Sergio Vera, Debora Gil, Agnes Borras, F. Javier Sanchez, Frederic Perez, Marius G. Linguraru, et al. (2012). "Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs " In H. Yoshida et al (Ed.), Workshop on Computational and Clinical Applications in Abdominal Imaging (Vol. 7029, 223–230). Lecture Notes in Computer Science. Berlin: Springer Link.
Abstract: Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D
objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial
manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our
method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs,
exploring the use of medial manifolds for the representation of multi-organ relations.
Keywords: medial manifolds, abdomen.
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Sergio Vera, Debora Gil, Agnes Borras, Marius George Linguraru, & Miguel Angel Gonzalez Ballester. (2013). "Geometric Steerable Medial Maps " . Machine Vision and Applications, 24(6), 1255–1266.
Abstract: In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume.
Keywords: Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction
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Sergio Vera, Debora Gil, Antonio Lopez, & Miguel Angel Gonzalez Ballester. (2012). "Multilocal Creaseness Measure " . The Insight Journal, .
Abstract: This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission.
Keywords: Ridges, Valley, Creaseness, Structure Tensor, Skeleton,
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Sergio Vera, Debora Gil, & Miguel Angel Gonzalez Ballester. (2014). "Anatomical parameterization for volumetric meshing of the liver " In SPIE – Medical Imaging (Vol. 9036).
Abstract: 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.
Keywords: Coordinate System; Anatomy Modeling; Parameterization
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