Symposium on Medical Information Processing and Analysis最新文献

Detecting Parkinson disease features with walking activity data 用步行活动数据检测帕金森病特征

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670234

C. C. Costa Filho, Lucas de Souza Barreto, Juliana Alves de Oliveira, Paulo Vitor de Castro Freitas, M. Costa

{"title":"Detecting Parkinson disease features with walking activity data","authors":"C. C. Costa Filho, Lucas de Souza Barreto, Juliana Alves de Oliveira, Paulo Vitor de Castro Freitas, M. Costa","doi":"10.1117/12.2670234","DOIUrl":"https://doi.org/10.1117/12.2670234","url":null,"abstract":"Due to aging of the population, some studies predict that the burden of Parkinson Disease (PD) will grow substantially in future decades. The rapid increase of PD will place a substantial burden on individuals, society, and health systems. In recent years, a series of works have been published on the use of mobile devices, equipped with sensors, such as accelerometers, gyroscopes and magnetometers to diagnosis and monitor PD outpatients . In this work, the influence of a series of factors on the diagnosis of Parkinson disease were evaluated, using walking activity data obtained from an mPower study. Through constructing several databases, the following factors were evaluated: dependent individual and independent individual approach, input record size, interleaved and non-interleaved data. In addition to these factors, the effect of the complexity of the CNN network on its performance was also evaluated. Databases with large records provided models with better performance in PD diagnosis than databases with small records. CNN's complexity also had a great impact on PD diagnosis performance. In this work, the best results achieved for the independent individual approach and for the dependent individual approach were an AUCROC of 0.511 and 0.861, respectively.","PeriodicalId":147201,"journal":{"name":"Symposium on Medical Information Processing and Analysis","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115820238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NEC-NET: segmentation and feature extraction network for the neurocranium in early childhood NEC-NET:儿童早期神经颅骨的分割与特征提取网络

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670281

Di Fan, N. Gajawelli, A. Paulli, Eryn Perry, J. Tanedo, S. Deoni, Yalin Wang, M. Linguraru, N. Lepore

引用次数: 0

Authentication of medical images through a hybrid watermarking method based on Hermite-Jigsaw-SVD 基于Hermite-Jigsaw-SVD混合水印方法的医学图像认证

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2669724

Sandra L. Gomez-Coronel, E. Moya-Albor, Karina Ruby Perez-Daniel, J. Brieva, I. Cruz-Aceves, A. Hernandez-Aguirre, J. Soto-Álvarez

{"title":"Authentication of medical images through a hybrid watermarking method based on Hermite-Jigsaw-SVD","authors":"Sandra L. Gomez-Coronel, E. Moya-Albor, Karina Ruby Perez-Daniel, J. Brieva, I. Cruz-Aceves, A. Hernandez-Aguirre, J. Soto-Álvarez","doi":"10.1117/12.2669724","DOIUrl":"https://doi.org/10.1117/12.2669724","url":null,"abstract":"This work presents a watermarking algorithm applied to medical images by using the Steered Hermite Transform (SHT), the Singular Value Decomposition (SVD), and the Jigsaw transform (JS). The principal objective is to protect the patient’s information using imperceptible watermarking and preserve its diagnosis. Thus, the watermark imperceptibility is achieved using the high-order Steered Hermite coefficients, whereas the SVD decomposition and the JS ensure the watermark against attacks. We use the medicine symbol Caduceus as a watermark. The metrics employed to evaluate the algorithm’s performance are the Peak Signal-to-Noise Ratio (PSNR), the Mean Structural Similarity Index (MSSIM), and the Normalized Cross-Correlation (NCC). The evaluation metrics over the watermarked image show that it does not suffer quantitative and qualitative changes, and the extracted watermark was recovered successfully with high PSNR values. In addition, several watermark extraction tests were performed against geometric and common processing attacks. These tests show that the proposed algorithm is robust under critical conditions of attacks, for example, against nonlinear smoothing (median filter), high noise addition (Gaussian and Salt & Pepper noise), high compression rates (JPEG compression), rotation between 0 to 180 degree, and translations up to 100 pixels.","PeriodicalId":147201,"journal":{"name":"Symposium on Medical Information Processing and Analysis","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122201936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of an acquisition system to monitoring asynchronous tele-ultrasound for lung patients 肺病人异步远程超声监测采集系统的研制

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670097

Esteban Avilés, Carlos Zegarra, Francis Reyes, Bejamin Castaneda, Stefano Enrique Romero

引用次数: 0

A named entity recognition framework using transformers to identify relevant clinical findings from mammographic radiological reports 一个命名实体识别框架，使用变压器从乳房x线摄影放射报告中识别相关临床发现

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670228

Eduardo Godoy, S. Chabert, Marvin Querales, J. Sotelo, Denis Parra, Carlos Fernández, Diego Mellado, A. Veloz, Scarlett Lever, Favian Pardo, Ayleen Bertini, Y. Molina, Claudia. C. Díaz, Rodrigo Ferreira, Rodrigo Salas

{"title":"A named entity recognition framework using transformers to identify relevant clinical findings from mammographic radiological reports","authors":"Eduardo Godoy, S. Chabert, Marvin Querales, J. Sotelo, Denis Parra, Carlos Fernández, Diego Mellado, A. Veloz, Scarlett Lever, Favian Pardo, Ayleen Bertini, Y. Molina, Claudia. C. Díaz, Rodrigo Ferreira, Rodrigo Salas","doi":"10.1117/12.2670228","DOIUrl":"https://doi.org/10.1117/12.2670228","url":null,"abstract":"Detecting and extracting findings in a radiological report is crucial for text mining tasks in several applications. In this case, a labeled process for the image associated with the radiological report in mammography and Spanish context for a computer vision model is required. This paper shows the methodology and process generated for this goal. This paper presents a Named Entity Recognition (NER) approach based on a transformer deep learning model, using a labeled corpus and fine-tuning process to find three concepts that compose a typical finding in a mammographic radiological report: laterality, location, and the finding. We add another concept in the labeled process, the negation, necessary to identify falses positive inside the text that writes the radiologist. Our model achieves an F1 score of 88.24% classifying the three principal concepts for a finding, product of the labeled and fine-tuning process. The results presented here will be used as input for future training work on a computer vision model.","PeriodicalId":147201,"journal":{"name":"Symposium on Medical Information Processing and Analysis","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124078042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Machine learning-based prediction of diabetes risk by combining exposome and electrocardiographic predictors 结合暴露和心电图预测的基于机器学习的糖尿病风险预测

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670078

Zeinab Shahbazi, Marina Camacho, Esmeralda Ruiz, A. Atehortúa, K. Lekadir

引用次数: 0

High-density electromyography as a method for estimating laryngeal muscle activity: a preliminary study 高密度肌电图作为估计喉肌活动的方法:初步研究

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670139

Josue Martínez, Oscar Valencia, M. Zañartu

{"title":"High-density electromyography as a method for estimating laryngeal muscle activity: a preliminary study","authors":"Josue Martínez, Oscar Valencia, M. Zañartu","doi":"10.1117/12.2670139","DOIUrl":"https://doi.org/10.1117/12.2670139","url":null,"abstract":"Current methods for monitoring laryngeal muscle function include techniques such as intramuscular electromyography, external laryngeal palpation, and laryngeal endoscopy. Although these methods have provided much information about muscle activation and function during voice production, they are invasive, uncomfortable, and subjective. The objective of this work is to explore the use of the high-density electromyography (HDsEMG) as a non-invasive alternative that can potentially provide objective information on the activity of the laryngeal muscles during speech. with a focus on the cricothyroid muscle (CT). From this set of signals, it is possible to decompose the electromyography signal, providing indirect information on the spatial recruitment and firing rates of motor units (MU) within the muscle. It is hypothesized that the use of MU firing rate and recruitment will allow for a better estimation of muscle activation compared to traditional methods. A high-density wireless HDsEMG equipment (Sessantaquattro, OT Bioelettronica) is used with a 64-channel electrode grid, which are centered on the CT muscle. Preliminary results of a case study illustrated that it was possible to obtain the rates and firing trains of 4 motor units. Future work will explore how HDsEMG applied to the larynx has the potential to improve diagnostic and therapeutic follow-up of pathologies of laryngeal function.","PeriodicalId":147201,"journal":{"name":"Symposium on Medical Information Processing and Analysis","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129375809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Group-wise cortical parcellation based on structural connectivity and hierarchical clustering 基于结构连通性和层次聚类的群体智能皮质分割

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670138

Joaquín Molina, Cristobal Mendoza, C. Román, J. Houenou, C. Poupon, J. F. Mangin, W. El-Deredy, C. Hernández, P. Guevara

{"title":"Group-wise cortical parcellation based on structural connectivity and hierarchical clustering","authors":"Joaquín Molina, Cristobal Mendoza, C. Román, J. Houenou, C. Poupon, J. F. Mangin, W. El-Deredy, C. Hernández, P. Guevara","doi":"10.1117/12.2670138","DOIUrl":"https://doi.org/10.1117/12.2670138","url":null,"abstract":"This paper presents a new cortical parcellation method based on group-wise connectivity and hierarchical clustering. A preliminary sub-parcellation is performed using intra-subject and inter-subject fiber clustering to obtain representative bundles among subjects with similar shapes and trajectories. The sub-parcellation is obtained by intersecting fiber clusters with cortical meshes. Next, mean connectivity and mean overlap matrices are computed over the sub-parcels to obtain spatial and connectivity information. To hierarchize the information, we propose to weight both matrices, to obtain an affinity graph, and then a dendrogram to merge or divide parcels by their hierarchy. Finally, to obtain homogeneous parcels, the method computes morphological operations. By selecting a different number of clusters over the dendrogram, the method obtains a different number of parcels and a variation in the resulting parcel sizes, depending on the parameters used. We computed the coefficient of variation (CV ) of the parcel size to evaluate the homogeneity of the parcels. Preliminary results suggest that the use of representative clusters and the integration of sub-parcel overlap and connectivity strength provide useful information to generate cortical parcellations at different levels of granularity. Even results are preliminary, this novel method allows researchers to add group-wise connectivity strength and spatial information for the construction of diffusion-based parcellations. Future work will include a detailed analysis of parameters, such as the matrix weights and the number of sub-parcel clusters, and the generation of hierarchical parcellations to improve the insight into the cortex subdivision and hierarchy among parcels.","PeriodicalId":147201,"journal":{"name":"Symposium on Medical Information Processing and Analysis","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131468984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Development of multiscale 3D residual U-Net to segment edematous adipose tissue by leveraging annotations from non-edematous adipose tissue 通过利用非水肿脂肪组织的注释，开发多尺度3D残余U-Net来分割水肿脂肪组织

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2669719

Jianfei Liu, O. Shafaat, R. Summers

{"title":"Development of multiscale 3D residual U-Net to segment edematous adipose tissue by leveraging annotations from non-edematous adipose tissue","authors":"Jianfei Liu, O. Shafaat, R. Summers","doi":"10.1117/12.2669719","DOIUrl":"https://doi.org/10.1117/12.2669719","url":null,"abstract":"Data annotation is often a prerequisite for applying deep learning to medical image segmentation. It is a tedious process that requires substantial guidance from experienced physicians. Adipose tissue labeling on CT scans is particularly time-consuming because adipose tissue is present throughout the entire body. One possible solution is to create inaccurate annotations from conventional (non-deep learning) adipose tissue segmentation methods. This work demonstrates the development of a deep learning model directly from these inaccurate annotations. The model is a multi-scale 3D residual U-Net where the encoder path is composed of residual blocks and the decoder path fuses multi-scale feature maps from different layers of decoder blocks. The training set consisted of 101 patients and the testing set consisted of 14 patients. Ten patients with anasarca were purposely added to the testing dataset as a stress test to evaluate model generality. Anasarca is a medical condition that leads to the generalized accumulation of edema within subcutaneous adipose tissue. Edema creates heterogeneity inside the adipose tissue which is absent in the training data. In comparison with a baseline method of manual annotations, the Dice coefficient improved significantly from 73.4 ± 14.1% to 80.2 ± 7.1% (p < 0.05). The model trained on inaccurate annotations improved the accuracy of adipose tissue segmentation by 7% without the need for any manual annotation.","PeriodicalId":147201,"journal":{"name":"Symposium on Medical Information Processing and Analysis","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133282965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Assessment of panoramic ultrasound reconstruction imaging using telemedicine equipment: a phantom experiment 利用远程医疗设备评估全景超声重建成像:模拟实验

Symposium on Medical Information Processing and Analysis Pub Date : 2023-03-06 DOI: 10.1117/12.2670069

Stefano Enrique Romero, Naomi Guevara, Ximena Montoya, B. Castañeda

{"title":"Assessment of panoramic ultrasound reconstruction imaging using telemedicine equipment: a phantom experiment","authors":"Stefano Enrique Romero, Naomi Guevara, Ximena Montoya, B. Castañeda","doi":"10.1117/12.2670069","DOIUrl":"https://doi.org/10.1117/12.2670069","url":null,"abstract":"Telemedicine is one of the most important technologies and services nowadays to overcome face-to-face consultation or intervention, especially, in rural areas. Teleultrasound monitoring is a service that has been useful for lung, thyroid or liver monitoring. In particular, one of the most promising protocols to attend this type of monitoring is sending asynchronous acquired ultrasound videos following the volume sweep imaging protocol; however, one of the main limitations is the poor internet bandwidth that does not allow sending files with a large amount of information. For this reason, in this work, it was proposed to send a single image that includes all the information of the acquisition using panoramic reconstruction of the ultrasound video. To perform the experiments, an ultrasound phantom was used with the commercially available ultrasound scanner with a linear transducer at different acquisition depths of 2.5, 3.7, 4.9, 6.1 and 7.4 cm. For the reconstructions, three phases were used detection of the acquisition moment, by means of optical flow; image processing for the selection of the region of interest and intensity adjustment; and panoramic reconstruction determining the displacement between frames. It was observed that this was successful for the deeper and higher contrast acquisitions.","PeriodicalId":147201,"journal":{"name":"Symposium on Medical Information Processing and Analysis","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132120898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0