A5073876341- Video Coding and Compression Technologies
- Remote-Sensing Image Classification
- Embedded Systems Design Techniques
- Advanced Data Compression Techniques
- Advanced Vision and Imaging
- Parallel Computing and Optimization Techniques
- Optical Imaging and Spectroscopy Techniques
- Green IT and Sustainability
- Image and Video Quality Assessment
- Brain Tumor Detection and Classification
- Spectroscopy Techniques in Biomedical and Chemical Research
- Advanced Image Fusion Techniques
- Multimedia Communication and Technology
- Interconnection Networks and Systems
- CCD and CMOS Imaging Sensors
- Advanced Chemical Sensor Technologies
- Spectroscopy and Chemometric Analyses
- Real-Time Systems Scheduling
- Advanced Wireless Network Optimization
- Photoacoustic and Ultrasonic Imaging
- Remote Sensing and Land Use
- Medical Image Segmentation Techniques
- Infrared Thermography in Medicine
- Image Enhancement Techniques
- Image and Signal Denoising Methods
Universidad Politécnica de Madrid
2016-2025
Indiana University School of Medicine
2024
Indiana University – Purdue University Indianapolis
2024
Software (Spain)
2014-2024
Research Institute Hospital 12 de Octubre
2020
National University of Distance Education
2018
Universidad Complutense de Madrid
2018
IMDEA Software
2013-2017
Universitat Politècnica de València
2013
École Polytechnique Fédérale de Lausanne
2000
Surgery for brain cancer is a major problem in neurosurgery. The diffuse infiltration into the surrounding normal by these tumors makes their accurate identification naked eye difficult. Since surgery common treatment cancer, an radical resection of tumor leads to improved survival rates patients. However, boundaries during challenging. Hyperspectral imaging non-contact, non-ionizing and non-invasive technique suitable medical diagnosis. This study presents development novel classification...
Hyperspectral imaging (HSI) allows for the acquisition of large numbers spectral bands throughout electromagnetic spectrum (within and beyond visual range) with respect to surface scenes captured by sensors. Using this information a set complex classification algorithms, it is possible determine which material or substance located in each pixel. The work presented paper aims exploit characteristics HSI develop demonstrator capable delineating tumor tissue from brain during neurosurgical...
The use of hyperspectral imaging for medical applications is becoming more common in recent years. One the main obstacles that researchers find when developing algorithms lack specific, publicly available, and data. work described this paper was developed within framework European project HELICoiD (HypErspectraL Imaging Cancer Detection), which had as a goal application to delineation brain tumors real-time during neurosurgical operations. In paper, methodology followed generate first...
Hyperspectral imaging techniques (HSI) do not require contact with patients and are non-ionizing as well non-invasive. As a consequence, they have been extensively applied in the medical field. HSI is being combined machine learning (ML) processes to obtain models assist diagnosis. In particular, combination of these has proven be reliable aid differentiation healthy tumor tissue during brain surgery. ML algorithms such support vector (SVM), random forest (RF) convolutional neural networks...
HIV incidence estimation is critical for monitoring the epidemic dynamics and effectiveness of public health prevention interventions. We aimed to identify sexual gender minorities (SGM) with recent infections, factors associated infection, estimate annualised rates.
<title>Abstract</title> <bold>Purpose</bold>: This study proposes a generalization of markerless patient registration in image-guided neurosurgery based on depth information. The work builds previous research to evaluate the performance range commercial cameras and two different algorithms this context. <bold>Methods</bold>: A multimodal experimental setup was used, testing five seven configurations. Fiducial Registration Error (FRE) Target (TRE) metrics were calculated using Iterative...
Dimensionality reduction represents a critical preprocessing step in order to increase the efficiency and performance of many hyperspectral imaging algorithms. However, dimensionality algorithms, such as Principal Component Analysis (PCA), suffer from their computationally demanding nature, becoming advisable for implementation onto high-performance computer architectures applications under strict latency constraints. This work presents PCA algorithm two different devices, namely, an NVIDIA...
The use of hyperspectral imaging (HSI) in the medical field is an emerging approach to assist physicians diagnostic or surgical guidance tasks. However, HSI data processing involves very high computational requirements due huge amount information captured by sensors. One stages with higher load K-Nearest Neighbors (KNN) filtering algorithm. main goal this study optimize and parallelize KNN algorithm exploiting GPU technology obtain real-time during brain cancer procedures. This parallel...
Over the last two decades, augmented reality (AR) has led to rapid development of new interfaces in various fields social and technological application domains. One such domain is medicine, a higher extent surgery, where these visualization techniques help improve effectiveness preoperative intraoperative procedures. Following this trend, paper presents SLIMBRAIN, real-time acquisition processing AR system suitable classify display brain tumor tissue from hyperspectral (HS) information. This...
High Efficiency Video Coding (HEVC) is a new video coding standard created by the JCT-VC group within ISO/IEC and ITU-T. HEVC targeted to provide same quality as H.264 at about half of bit-rate will replace soon its predecessor in multimedia consumer applications. Up now, only few decoder implementations have been reported, most them oriented carry out complexity analysis. In this paper, DSP-based implementation HM9.0 presented. best our knowledge, it first shown scientific literature....
For enabling virtual reality on natural content, Depth Image-Based Rendering (DIBR) techniques have been steadily developed over the past decade, but their quality highly depends that of depth estimation. This paper is an attempt to deliver good-quality Estimation Reference Software (DERS) well-structured for further use in worldwide MPEG standardization committee.The existing DERS has refactored, debugged and extended any number input views generating accurate maps. Their validated by...
Magnetic resonance imaging (MRI) is a common technique in image-guided neurosurgery (IGN). Recent research explores the integration of methods like ultrasound and tomography, among others, with hyperspectral (HS) gaining attention due to its non-invasive real-time tissue classification capabilities. The main challenge registration process, often requiring manual intervention. This work introduces an automatic, markerless method for aligning HS images MRI.
Latest generation DSPs are becoming more efficient, being able to improve their forerunners while reducing internal memory size lower the cost. In this paper, an H.264 video decoder based on a latest DSP is described. Both EDMA and architecture of processor have been fully exploited increase execution speed. Profiling tests carried out by using digital TV streams DVD transcoded sequences. The speed new running 16% better than that forerunner with 20% same decoder.
During the last decades, new video compression standards arose every few years with always higher gains and considerable increases on computational cost. Single core processors have reached their limit multicore are there to overcome this issue give more processing power. In order accelerate implementation of coding standards, MPEG has standardized an alternative framework describe decoders. It is based reference decoders written in RVC CAL dataflow actor language. From these descriptions, a...
In this paper, the implementation of a digital signal processor (DSP) based H.264 decoder for multi-format set-top box is described. Baseline and main profiles are supported. Using several software optimization techniques, has been fitted into low-cost DSP. The alone tested in simulation, achieving real-time performance with 600 MHz system clock. Moreover, it integrated IP allowing actual environment tests excellent results. Finally, ported to latest generation
Current computational demands require increasing designer's efficiency and system performance per watt. A broadly accepted solution for efficient accelerators implementation is reconfigurable computing. However, typical HDL methodologies very specific skills a considerable amount of time. Despite the new approaches to high-level synthesis like OpenCL, given large heterogeneity in today's devices (manycore, CPUs, GPUs, FPGAs), there no one-fits-all solution, so maximize performance,...
Currently, the usefulness of many mobile systems is largely limited by battery lifetime. In this paper, energy-based fair queuing (EFQ) proposed as a pivotal instrument to maximize user experience in type system. Energy-based novel class energy-aware scheduling algorithms that support proportional energy use, effective time-constraint compliance and flexible trade-off between them. The combination EFQ with lifetime-oriented power management schemes opens door battery-limited systems....
Video coding is one of the most demanding applications, in terms computational cost, for portable multimedia terminals. In last years, new video standards, like High Efficiency Coding (HEVC), and increasing resolutions codecs have overtaken capacities single core processors embedded systems. consequence, multicore architectures are used current Besides, methodologies frameworks arising to speed-up design cycle. this paper, a methodology based on Reconfigurable CAL Actor Language (RVC-CAL)...