Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ IEEE Accessarrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
IEEE Access
Article . 2020 . Peer-reviewed
License: CC BY
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
IEEE Access
Article
License: CC BY
Data sources: UnpayWall
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
IEEE Access
Article . 2020
Data sources: DOAJ
https://dx.doi.org/10.60692/6c...
Other literature type . 2020
Data sources: Datacite
https://dx.doi.org/10.60692/0y...
Other literature type . 2020
Data sources: Datacite
DBLP
Article
Data sources: DBLP
versions View all 5 versions
addClaim

This Research product is the result of merged Research products in OpenAIRE.

You have already added 0 works in your ORCID record related to the merged Research product.

Towards a Low Complexity Scheme for Medical Images in Scalable Video Coding

نحو نظام منخفض التعقيد للصور الطبية في ترميز الفيديو القابل للتطوير
Authors: Muhammad Shoaib; Muhammad Imran; Fazli Subhan; Iftikhar Ahmad;

Towards a Low Complexity Scheme for Medical Images in Scalable Video Coding

Abstract

L'imagerie médicale est devenue d'une importance vitale pour le diagnostic des maladies et la réalisation de procédures non invasives. Les progrès dans les applications de cybersanté sont remis en question par le fait que l'imagerie numérique et les communications en médecine (DICOM) nécessitent des images à haute résolution, augmentant ainsi leur taille et la complexité de calcul associée, en particulier lorsque ces images sont communiquées sur des réseaux IP et sans fil. Par conséquent, la recherche médicale nécessite une technique de codage efficace pour obtenir des images de haute qualité et de faible complexité avec des caractéristiques résilientes aux erreurs. Dans cette étude, nous proposons un schéma de codage amélioré qui exploite les caractéristiques de contenu des vidéos codées de faible complexité combinées à un ordonnancement flexible des macroblocs pour la résilience aux erreurs. Nous identifions la région homogène dans laquelle la recherche de modes de macroblocs optimaux est terminée prématurément. Pour les régions non homogènes, l'intégration de blocs plus petits n'est employée que si la différence vectorielle est inférieure au seuil. Les résultats confirment que la technique proposée réalise une amélioration considérable des performances par rapport aux schémas existants en termes de réduction de la complexité de calcul sans compromettre le débit binaire et le rapport signal/bruit de crête.

Las imágenes médicas se han vuelto de vital importancia para diagnosticar enfermedades y realizar procedimientos no invasivos. Los avances en las aplicaciones de eHealth se ven desafiados por el hecho de que Digital Imaging and Communications in Medicine (DICOM) requiere imágenes de alta resolución, lo que aumenta su tamaño y la complejidad computacional asociada, particularmente cuando estas imágenes se comunican a través de redes IP e inalámbricas. Por lo tanto, la investigación médica requiere una técnica de codificación eficiente para lograr imágenes de alta calidad y baja complejidad con características resistentes a errores. En este estudio, proponemos un esquema de codificación mejorado que explota las características de contenido de videos codificados con baja complejidad combinados con un ordenamiento de macrobloques flexible para la resistencia a errores. Identificamos la región homogénea en la que se termina anticipadamente la búsqueda de modos óptimos de macrobloque. Para regiones no homogéneas, la integración de bloques más pequeños se emplea solo si la diferencia vectorial es menor que el umbral. Los resultados confirman que la técnica propuesta logra una mejora considerable del rendimiento en comparación con los esquemas existentes en términos de reducción de la complejidad computacional sin comprometer la tasa de bits y la relación señal/ruido pico.

Medical imaging has become of vital importance for diagnosing diseases and conducting noninvasive procedures. Advances in eHealth applications are challenged by the fact that Digital Imaging and Communications in Medicine (DICOM) requires high-resolution images, thereby increasing their size and the associated computational complexity, particularly when these images are communicated over IP and wireless networks. Therefore, medical research requires an efficient coding technique to achieve high-quality and low-complexity images with error-resilient features. In this study, we propose an improved coding scheme that exploits the content features of encoded videos with low complexity combined with flexible macroblock ordering for error resilience. We identify the homogeneous region in which the search for optimal macroblock modes is early terminated. For non-homogeneous regions, the integration of smaller blocks is employed only if the vector difference is less than the threshold. Results confirm that the proposed technique achieves a considerable performance improvement compared with existing schemes in terms of reducing the computational complexity without compromising the bit-rate and peak signal-to-noise ratio.

أصبح التصوير الطبي ذا أهمية حيوية لتشخيص الأمراض وإجراء الإجراءات غير الجراحية. تواجه التطورات في تطبيقات الصحة الإلكترونية تحديات بسبب حقيقة أن التصوير الرقمي والاتصالات في الطب (DICOM) تتطلب صورًا عالية الدقة، وبالتالي زيادة حجمها والتعقيد الحسابي المرتبط بها، خاصة عندما يتم توصيل هذه الصور عبر بروتوكول الإنترنت والشبكات اللاسلكية. لذلك، تتطلب الأبحاث الطبية تقنية ترميز فعالة لتحقيق صور عالية الجودة ومنخفضة التعقيد مع ميزات مقاومة للأخطاء. في هذه الدراسة، نقترح مخطط ترميز محسّن يستغل ميزات محتوى مقاطع الفيديو المشفرة ذات التعقيد المنخفض جنبًا إلى جنب مع كتلة الماكرو المرنة التي تطلب مرونة الخطأ. نحدد المنطقة المتجانسة التي يتم فيها إنهاء البحث عن أوضاع الكتلة الكلية المثلى في وقت مبكر. بالنسبة للمناطق غير المتجانسة، لا يتم استخدام تكامل الكتل الأصغر إلا إذا كان فرق المتجه أقل من العتبة. تؤكد النتائج أن التقنية المقترحة تحقق تحسنًا كبيرًا في الأداء مقارنة بالمخططات الحالية من حيث تقليل التعقيد الحسابي دون المساس بمعدل البت ونسبة إشارة الذروة إلى الضوضاء.

Keywords

Artificial intelligence, scalable video coding, medical imaging, Advancements in Video Coding Standards and Techniques, slice coding, Mathematical analysis, low complexity, Database, Theoretical computer science, FOS: Mathematics, Image Compression Techniques and Standards, Scalable Video Coding, Image Quality Assessment in Multimedia Content, Error Resilient Coding, Scheme (mathematics), Coding (social sciences), Statistics, High Efficiency Video Coding (HEVC), Scalability, Computer science, TK1-9971, Computer Science, Physical Sciences, Signal Processing, eHealth, flexible macroblock ordering, Computer vision, Electrical engineering. Electronics. Nuclear engineering, Computer Vision and Pattern Recognition, Mathematics, Video Coding, Stereoscopic Images

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    4
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
gold