resst - seunet++:磁共振成像(MRI)图像中左心室和心肌精确分割的深度模型。

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL
Abduljabbar S Ba Mahel, Mehdhar S A M Al-Gaashani, Fahad Mushabbab G Alotaibi, Reem Ibrahim Alkanhel
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引用次数: 0

摘要

高度精确和可靠的左心室(LV)和心肌分割对于诊断和治疗心血管疾病至关重要,其中包括持续性微血管阻塞(MVO)和心肌梗死(MI)疾病。这一过程提高了诊断的准确性,优化了治疗干预措施的规划和实施,最终提高了护理质量和患者预后。早期研究的局限性包括忽略了在MRI中准确描绘左室和心肌(Myo)区域所需的复杂图像预处理,以及缺乏大量高质量的数据集。因此,本文提出了一个全面的端到端框架,其中包括对比度有限的自适应直方图均衡化(CLAHE)和双边滤波方法用于图像预处理,并开发和实现了一种用于左心室和心肌分割的深度模型。本研究利用EMIDEC数据库对模型进行训练和评估,允许与六种最先进的(SOTA)分割模型进行详细的比较分析。这种方法为心血管疾病的诊断和治疗提供了高准确性和可靠性的分割。该模型的分割率均值较高,如IoU分割率为93.73%,召回率为96.54%,骰子系数为96.70%,精度为96.86%,f1分数为96.70%。为了验证该模型的泛化能力,我们在五个补充数据库上对该模型进行了评估,证实了该模型在不同环境下的卓越效率和适应性。所提出的研究结果表明,所提出的深度模型超越了目前的方法,提供了更精确和有弹性的心脏结构分割。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ResST-SEUNet++: Deep Model for Accurate Segmentation of Left Ventricle and Myocardium in Magnetic Resonance Imaging (MRI) Images.

The highly precise and trustworthy segmentation of the left ventricle (LV) and myocardium is critical for diagnosing and treating cardiovascular disorders, which includes persistent microvascular obstruction (MVO) as well as myocardial infarction (MI) diseases. This process improves diagnostic accuracy and optimizes the planning and implementation of therapeutic interventions, ultimately improving the quality of care and patient prognosis. Limitations of earlier investigations include neglecting the complex image pre-processing required to accurately delineate areas of the LV and myocardium (Myo) in MRI and the absence of a substantial, high-quality dataset. Thus, this paper presents a comprehensive end-to-end framework, which includes contrast-limited adaptive histogram equalization (CLAHE) and bilateral filtering methods for image pre-processing and the development and implementation of a proposed deep model for left ventricular and myocardium segmentation. This study utilizes the EMIDEC database for the training and assessment of the model, allowing for a detailed comparative analysis with six state-of-the-art (SOTA) segmentation models. This approach provides a high accuracy and reliability for the segmentation that is crucial for the diagnosis and treatment of cardiovascular disorders. The achievements of the proposed model are demonstrated by high average values of segmentation rates, such as an Intersection over Union (IoU) of 93.73%, Recall of 96.54%, Dice coefficient of 96.70%, Precision of 96.86%, and F1-score of 96.70%. To verify the generalization capability, we assessed our suggested model on five supplementary databases, which substantiates its exceptional efficiency and adaptability in a diverse environment. The presented findings demonstrate that the proposed deep model surpasses current methods, offering more a precise and resilient segmentation of cardiac structures.

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来源期刊
Bioengineering
Bioengineering Chemical Engineering-Bioengineering
CiteScore
4.00
自引率
8.70%
发文量
661
期刊介绍: Aims Bioengineering (ISSN 2306-5354) provides an advanced forum for the science and technology of bioengineering. It publishes original research papers, comprehensive reviews, communications and case reports. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. All aspects of bioengineering are welcomed from theoretical concepts to education and applications. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. There are, in addition, four key features of this Journal: ● We are introducing a new concept in scientific and technical publications “The Translational Case Report in Bioengineering”. It is a descriptive explanatory analysis of a transformative or translational event. Understanding that the goal of bioengineering scholarship is to advance towards a transformative or clinical solution to an identified transformative/clinical need, the translational case report is used to explore causation in order to find underlying principles that may guide other similar transformative/translational undertakings. ● Manuscripts regarding research proposals and research ideas will be particularly welcomed. ● Electronic files and software regarding the full details of the calculation and experimental procedure, if unable to be published in a normal way, can be deposited as supplementary material. ● We also accept manuscripts communicating to a broader audience with regard to research projects financed with public funds. Scope ● Bionics and biological cybernetics: implantology; bio–abio interfaces ● Bioelectronics: wearable electronics; implantable electronics; “more than Moore” electronics; bioelectronics devices ● Bioprocess and biosystems engineering and applications: bioprocess design; biocatalysis; bioseparation and bioreactors; bioinformatics; bioenergy; etc. ● Biomolecular, cellular and tissue engineering and applications: tissue engineering; chromosome engineering; embryo engineering; cellular, molecular and synthetic biology; metabolic engineering; bio-nanotechnology; micro/nano technologies; genetic engineering; transgenic technology ● Biomedical engineering and applications: biomechatronics; biomedical electronics; biomechanics; biomaterials; biomimetics; biomedical diagnostics; biomedical therapy; biomedical devices; sensors and circuits; biomedical imaging and medical information systems; implants and regenerative medicine; neurotechnology; clinical engineering; rehabilitation engineering ● Biochemical engineering and applications: metabolic pathway engineering; modeling and simulation ● Translational bioengineering
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