Dr. César Sanz Álvaro Profile

Dr. César Sanz Álvaro

at Universidad Politécnica de Madrid

SPIE Involvement:

Author

SPIE Journal Paper | 24 September 2024 Open Access

Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification

Alberto Martín-Pérez, Alejandro Martinez de Ternero, Alfonso Lagares, Eduardo Juarez, César Sanz

JBO, Vol. 29, Issue 09, 093510, (September 2024) https://doi.org/10.1117/12.10.1117/1.JBO.29.9.093510

KEYWORDS: Cameras, Tissues, Line scan image sensors, Brain, Reflectivity, Chromophores, In vivo imaging, Tumors, Sensors, Neuroimaging

Read Abstract +

SignificanceHyperspectral imaging sensors have rapidly advanced, aiding in tumor diagnostics for in vivo brain tumors. Linescan cameras effectively distinguish between pathological and healthy tissue, whereas snapshot cameras offer a potential alternative to reduce acquisition time.AimOur research compares linescan and snapshot hyperspectral cameras for in vivo brain tissues and chromophore identification.ApproachWe compared a linescan pushbroom camera and a snapshot camera using images from 10 patients with various pathologies. Objective comparisons were made using unnormalized and normalized data for healthy and pathological tissues. We utilized the interquartile range (IQR) for the spectral angle mapping (SAM), the goodness-of-fit coefficient (GFC), and the root mean square error (RMSE) within the 659.95 to 951.42 nm range. In addition, we assessed the ability of both cameras to capture tissue chromophores by analyzing absorbance from reflectance information.ResultsThe SAM metric indicates reduced dispersion and high similarity between cameras for pathological samples, with a 9.68% IQR for normalized data compared with 2.38% for unnormalized data. This pattern is consistent across GFC and RMSE metrics, regardless of tissue type. Moreover, both cameras could identify absorption peaks of certain chromophores. For instance, using the absorbance measurements of the linescan camera, we obtained SAM values below 0.235 for four peaks, regardless of the tissue and type of data under inspection. These peaks are one for cytochrome b in its oxidized form at λ=422 nm, two for HbO2 at λ=542 nm and λ=576 nm, and one for water at λ=976 nm.ConclusionThe spectral signatures of the cameras show more similarity with unnormalized data, likely due to snapshot sensor noise, resulting in noisier signatures post-normalization. Comparisons in this study suggest that snapshot cameras might be viable alternatives to linescan cameras for real-time brain tissue identification.

DOWNLOAD PAPER

Proceedings Article | 5 October 2017 Paper

Parallel exploitation of a spatial-spectral classification approach for hyperspectral images on RVC-CAL

R. Lazcano, D. Madroñal, H. Fabelo, S. Ortega, R. Salvador, G. Callicó, E. Juárez, C. Sanz

Proceedings Volume 10430, 104300A (2017) https://doi.org/10.1117/12.2279613

KEYWORDS: Hyperspectral imaging, Image classification, Image processing, Principal component analysis, Algorithm development, Machine learning, Parallel processing

Read Abstract +

Proceedings Article | 24 October 2016 Presentation + Paper

Parallel implementation of a hyperspectral image linear SVM classifier using RVC-CAL

D. Madroñal , H. Fabelo, R. Lazcano, G. M. Callicó, E. Juárez, C. Sanz

Proceedings Volume 10007, 1000709 (2016) https://doi.org/10.1117/12.2241648

KEYWORDS: Hyperspectral imaging, Image processing, Spectral resolution, Ultraviolet radiation, Remote sensing, Infrared imaging, Information security, Analytical research, Binary data, Classification systems

Read Abstract +

Proceedings Article | 24 October 2016 Presentation + Paper

Parallelism exploitation of a PCA algorithm for hyperspectral images using RVC-CAL

R. Lazcano, I. Sidrach-Cardona , D. Madroñal, K. Desnos, M. Pelcat, E. Juárez, C. Sanz

Proceedings Volume 10007, 100070H (2016) https://doi.org/10.1117/12.2241643

KEYWORDS: Principal component analysis, Hyperspectral imaging, Sensors, Data processing, Image processing, Electromagnetism, Remote sensing, Data modeling, Chemical elements, Spatial resolution

Read Abstract +

Hyperspectral imaging (HI) collects information from across the electromagnetic spectrum, covering a wide range of wavelengths. The tremendous development of this technology within the field of remote sensing has led to new research fields, such as cancer automatic detection or precision agriculture, but has also increased the performance requirements of the applications. For instance, strong time constraints need to be respected, since many applications imply real-time responses. Achieving real-time is a challenge, as hyperspectral sensors generate high volumes of data to process. Thus, so as to achieve this requisite, first the initial image data needs to be reduced by discarding redundancies and keeping only useful information. Then, the intrinsic parallelism in a system specification must be explicitly highlighted.

In this paper, the PCA (Principal Component Analysis) algorithm is implemented using the RVC-CAL dataflow language, which specifies a system as a set of blocks or actors and allows its parallelization by scheduling the blocks over different processing units. Two implementations of PCA for hyperspectral images have been compared when aiming at obtaining the first few principal components: first, the algorithm has been implemented using the Jacobi approach for obtaining the eigenvectors; thereafter, the NIPALS-PCA algorithm, which approximates the principal components iteratively, has also been studied. Both implementations have been compared in terms of accuracy and computation time; then, the parallelization of both models has also been analyzed.

These comparisons show promising results in terms of computation time and parallelization: the performance of the NIPALS-PCA algorithm is clearly better when only the first principal component is achieved, while the partitioning of the algorithm execution over several cores shows an important speedup for the PCA-Jacobi. Thus, experimental results show the potential of RVC–CAL to automatically generate implementations which process in real-time the large volumes of information of hyperspectral sensors, as it provides advanced semantics for exploiting system parallelization.

Proceedings Article | 20 October 2015 Paper

Dimensionality reduction and endmember extraction for hyperspectral imaging using an RVC-CAL library

D. Madroñal Quintín, R. Lazcano López, E. Juárez Martínez, C. Sanz Álvaro

Proceedings Volume 9646, 964604 (2015) https://doi.org/10.1117/12.2195093

KEYWORDS: Hyperspectral imaging, Algorithm development, Image processing, Principal component analysis, Surgery, Chemical elements, Cancer, Infrared imaging, Infrared radiation, Ultraviolet radiation

Read Abstract +

Proceedings Article | 20 October 2015 Paper

RVC-CAL library for endmember and abundance estimation in hyperspectral image analysis

R. Lazcano López, D. Madroñal Quintín, E. Juárez Martínez, C. Sanz Álvaro

Proceedings Volume 9646, 964609 (2015) https://doi.org/10.1117/12.2194888

KEYWORDS: Hyperspectral imaging, Image processing, Algorithm development, Image analysis, Signal to noise ratio, Cancer, Surgery, Matrices, Analytical research, Remote sensing

Read Abstract +

Hyperspectral imaging (HI) collects information from across the electromagnetic spectrum, covering a wide range of wavelengths. Although this technology was initially developed for remote sensing and earth observation, its multiple advantages - such as high spectral resolution - led to its application in other fields, as cancer detection. However, this new field has shown specific requirements; for instance, it needs to accomplish strong time specifications, since all the potential applications - like surgical guidance or in vivo tumor detection - imply real-time requisites. Achieving this time requirements is a great challenge, as hyperspectral images generate extremely high volumes of data to process. Thus, some new research lines are studying new processing techniques, and the most relevant ones are related to system parallelization.

In that line, this paper describes the construction of a new hyperspectral processing library for RVC–CAL language, which is specifically designed for multimedia applications and allows multithreading compilation and system parallelization. This paper presents the development of the required library functions to implement two of the four stages of the hyperspectral imaging processing chain--endmember and abundances estimation. The results obtained show that the library achieves speedups of 30%, approximately, comparing to an existing software of hyperspectral images analysis; concretely, the endmember estimation step reaches an average speedup of 27.6%, which saves almost 8 seconds in the execution time. It also shows the existence of some bottlenecks, as the communication interfaces among the different actors due to the volume of data to transfer. Finally, it is shown that the library considerably simplifies the implementation process. Thus, experimental results show the potential of a RVC–CAL library for analyzing hyperspectral images in real-time, as it provides enough resources to study the system performance.

Proceedings Article | 3 May 2011 Paper

Energy consumption estimation of an OMAP-based Android operating system

Gabriel González, Eduardo Juárez, Juan José Castro, César Sanz

Proceedings Volume 8067, 80670V (2011) https://doi.org/10.1117/12.888264

KEYWORDS: Digital signal processing, Signal processing, Multimedia, Operating systems, Video, Embedded systems, Video processing, Clocks, Process modeling, Manufacturing

Read Abstract +

Proceedings Article | 28 May 2009 Paper

A system for emulating the broadcasting of a DAB ensemble containing data services

David Samper, Pedro Lobo, Manuel César Rodríguez, César Sanz

Proceedings Volume 7363, 73630J (2009) https://doi.org/10.1117/12.821490

KEYWORDS: Receivers, Interfaces, Video, Transmitters, Error control coding, Prototyping, Standards development, Field programmable gate arrays, Human-machine interfaces, Transceivers

Read Abstract +

Proceedings Article | 28 May 2009 Paper

Implementation of a media synchronization algorithm for multistandard IP set-top box systems

Esther Estévez, David Samper, Fernando Pescador, Eduardo Juárez, César Sanz

Proceedings Volume 7363, 73630L (2009) https://doi.org/10.1117/12.821641

KEYWORDS: Video, Digital signal processing, Clocks, Photoemission spectroscopy, Computer programming, Computer architecture, Receivers, Multimedia, Digital video discs, On-screen displays

Read Abstract +

Proceedings Article | 10 May 2007 Paper

Multiformat decoder for a DSP-based IP set-top box

F. Pescador, M. J. Garrido, C. Sanz, E. Juárez, D. Samper, R. Antoniello

Proceedings Volume 6590, 65900Z (2007) https://doi.org/10.1117/12.722287

KEYWORDS: Digital signal processing, Video, Surface plasmons, Digital video discs, Clocks, Internet, Computer programming, Video coding, Computer architecture, Data storage

Read Abstract +

Showing 5 of 10 publications

Conference Committee Involvement (4)

VLSI Circuits and Systems

18 April 2011 | Prague, Czech Republic

VLSI Circuits and Systems

4 May 2009 | Dresden, Germany

VLSI Circuits and Systems

2 May 2007 | Maspalomas, Gran Canaria, Spain

VLSI Circuits and Systems

19 May 2003 | Maspalomas, Gran Canaria, Canary Islands, Spain

Keywords/Phrases

Search In:

Publication Years