基于PACS的以数字化影像征象分类为模块的教学系统的研究与应用

目的研究基于PACS的以数字化影像征象分类为模块的教学系统及临床应用。方法在PACS系统中，允许每一权限医生对典型病例图像注释后按影像征象进行归类，然后存储于SQLSERVER2000服务器中，采用模块化管理方式，归类的影像征象按临床实践要求分析其病理过程、可能的疾病及其鉴别诊断方法。在专业的显示器（或个人计算机）上，通过用户界面输入解剖部位／影像征象即可调阅相关图像进行教学，弘要时通过Intrartet或Interilet实现网络教学。结果 系统开放性、稳定性好，影像数据和信息能安全、无损的存储，传输速度快，操作互动性好。结论基于PACS的以数字化影像征象分类为模块的教学系统符合临床实践过程要求，具有直观、实用性强，操作简便，图像安全可靠等优点，便于临床影像教学工作的开展。     

基于文献的慢性萎缩性胃炎胃镜像与中医辨证的相关性研究

目的 探索慢性萎缩性胃炎(CAG)胃镜像与中医辨证的相关性,提高临床对CAG辨证的准确性。方法 对CAG现代文献进行研究整理,在中国知网(CNKI)、万方、维普、中国生物医学文献数据库(CBM)、PubMed、EMBase、Cochrane Library数据库中检索建库-2022年8月1日涉及CAG中医辨证分型及胃镜像描述的文献,筛选合格文献,提取CAG患者的中医证型、胃镜像等信息,整理数据后建立数据库,应用SPSS 20.0软件进行相关性分析。结果 纳入合格文献10篇,纳入有效病例1 562例,涉及中医证型5种。中医辨证分型按频次高低依次为肝胃不和证、脾胃虚弱证、脾胃湿热证、胃络瘀阻证、胃阴不足证。胃镜像检出率以黏膜白相最高,为47.38%。黏膜白相以脾胃虚弱证检出率最高,黏膜粗糙、充血、水肿、颗粒增生、血管显露、结节隆起均在胃络瘀阻证中检出率最高;黏膜出血、糜烂以脾胃湿热证检出率最高;皱襞变平、黏膜灰白色以胃阴不足证检出率最高;胆汁反流以肝胃不和证检出率最高。结论 中医辨证与部分胃镜像具有相关性,基于胃镜像的CAG中医辨证规律总结如下:镜下出现黏膜白相、皱襞变平,考虑为脾胃虚弱证或胃阴不足证,胃阴不足证兼见黏膜灰白;镜下出现胆汁反流,考虑为肝胃不和证、脾胃湿热证,肝胃不和证多兼见黏膜充血、水肿,脾胃湿热证多兼见黏膜糜烂;镜下出现颗粒增生、结节隆起,考虑为胃络瘀阻证。     

Application of Morphological Bit Planes in Retinal Blood Vessel Extraction

The appearance of the retinal blood vessels is an important diagnostic indicator of various clinical disorders of the eye and the body. Retinal blood vessels have been shown to provide evidence in terms of change in diameter, branching angles, or tortuosity, as a result of ophthalmic disease. This paper reports the development for an automated method for segmentation of blood vessels in retinal images. A unique combination of methods for retinal blood vessel skeleton detection and multidirectional morphological bit plane slicing is presented to extract the blood vessels from the color retinal images. The skeleton of main vessels is extracted by the application of directional differential operators and then evaluation of combination of derivative signs and average derivative values. Mathematical morphology has been materialized as a proficient technique for quantifying the retinal vasculature in ocular fundus images. A multidirectional top-hat operator with rotating structuring elements is used to emphasize the vessels in a particular direction, and information is extracted using bit plane slicing. An iterative region growing method is applied to integrate the main skeleton and the images resulting from bit plane slicing of vessel direction-dependent morphological filters. The approach is tested on two publicly available databases DRIVE and STARE. Average accuracy achieved by the proposed method is 0.9423 for both the databases with significant values of sensitivity and specificity also; the algorithm outperforms the second human observer in terms of precision of segmented vessel tree.     

Optimization of breast lesion segmentation in texture feature space approach

This paper develops a method for semi-automatic detection of breast lesion boundaries by combining the snake evolution techniques with statistical texture information of images. We propose an efficient image energy function in segmentation based on image features, first-order textural features and four n × n masks. The segmentation results were evaluated by using area error rate. The image features were evaluated qualitatively by using the contrast-to-noise ratio and fractal dimension analysis. In our study, standard deviation, skewness and entropy are indicated as being the most relevant image features.     

Application of artificial intelligence using a novel EUS-based convolutional neural network model to identify and distinguish benign and malignant hepatic masses

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Interrogating the microenvironmental landscape of tumors with computational image analysis approaches

The tumor microenvironment is an interacting heterogeneous collection of cancer cells, resident as well as infiltrating host cells, secreted factors, and extracellular matrix proteins. With the growing importance of immunotherapies, it has become crucial to be able to characterize the composition and the functional orientation of the microenvironment. The development of novel computational image analysis methodologies may enable the robust quantification and localization of immune and related biomarker-expressing cells within the microenvironment. The aim of the review is to concisely highlight a selection of current and significant contributions pertinent to methodological advances coupled with biomedical or translational applications. A further aim is to concisely present computational advances that, to our knowledge, have currently very limited use for the assessment of the microenvironment but have the potential to enhance image analysis pipelines; on this basis, an example is shown for the detection and segmentation of cells of the microenvironment using a published pipeline and a public dataset. Finally, a general proposal is presented on the conceptual design of automation-optimized computational image analysis workflows in the biomedical and clinical domain.     

Multinodular and Vacuolating Neuronal Tumor of the Cerebrum (MVNT): A case series and review of the literature

Background and purposeMultinodular and Vacuolating Neuronal Tumor of the cerebrum (MVNT) is a benign –seizure associated– lesion affecting mostly adults. This new entity has been included in the 2016 World Health Organization classification of tumors of the central nervous system.Its pathologic hallmark consist of a subcortical cluster of nodular lesions located on the subcortical white matter.We aim to report a series of cases of presumed MVNT observed in our institution and review the literature.Materials and methodsIn this retrospective study, a search was performed on our hospital information system. Sixteen cases were included. Demographic, clinical and radiological features were detailed in a table.All patients had an MRI acquired either on a 1.5 or a 3 Tesla scanner. Sequences performed included T1, T2, GRE/SWI, T2 FLAIR and DWI. Gadolinium enhanced T1-WI wer available in 11 patients and follow-up MRI were available in 7 patients.ResultsPatient ages ranged from 16 to 77 years (mean 42 years). Seizure and non-focal headache were by far the most common neurological complaints for which MRI was requested. All lesions consisted of clusters of multiple, discrete, round or ovoid, intra-axial, FLAIR and T2-WI hyperintense nodules. Follow-up MRI scans showed no changes between studies.ConclusionsMVNT is a benign, stable lesion that exhibits a typical radiological pattern that most of the times sufficed to arrive to a diagnosis, without the need of pathological confirmation. We confirm that our demographic, clinical and radiological findings are in accordance with those published in international literature.