{"title":"Filtered Trajectory Recovery: A Continuous Extension to Event-Based Model for Alzheimer's Disease Progression Modeling","authors":"Jiangchuan Du, Yuan Zhou","doi":"10.1007/978-3-031-34048-2_8","DOIUrl":"https://doi.org/10.1007/978-3-031-34048-2_8","url":null,"abstract":"","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"1 1","pages":"95-106"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75473731","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}
Xiaodong Wu, Leixin Zhou, F. Zaman, B. Qiu, J. Buatti
{"title":"Model-Informed Deep Learning for Surface Segmentation in Medical Imaging","authors":"Xiaodong Wu, Leixin Zhou, F. Zaman, B. Qiu, J. Buatti","doi":"10.1007/978-3-031-34048-2_63","DOIUrl":"https://doi.org/10.1007/978-3-031-34048-2_63","url":null,"abstract":"","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"46 1","pages":"822-834"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81145586","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}
{"title":"Information Processing in Medical Imaging: 28th International Conference, IPMI 2023, San Carlos de Bariloche, Argentina, June 18–23, 2023, Proceedings","authors":"","doi":"10.1007/978-3-031-34048-2","DOIUrl":"https://doi.org/10.1007/978-3-031-34048-2","url":null,"abstract":"","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78651196","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}
Jianghao Wu, Ran Gu, Tao Lu, Shaoting Zhang, Guotai Wang
{"title":"UPL-TTA: Uncertainty-Aware Pseudo Label Guided Fully Test Time Adaptation for Fetal Brain Segmentation","authors":"Jianghao Wu, Ran Gu, Tao Lu, Shaoting Zhang, Guotai Wang","doi":"10.1007/978-3-031-34048-2_19","DOIUrl":"https://doi.org/10.1007/978-3-031-34048-2_19","url":null,"abstract":"","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"4 1","pages":"237-249"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83209823","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}
Huan Liu, Tingting Dan, Zhuobin Huang, Defu Yang, Won Hwa Kim, Minjeong Kim, P. Laurienti, Guorong Wu
{"title":"HoloBrain: A Harmonic Holography for Self-organized Brain Function","authors":"Huan Liu, Tingting Dan, Zhuobin Huang, Defu Yang, Won Hwa Kim, Minjeong Kim, P. Laurienti, Guorong Wu","doi":"10.1007/978-3-031-34048-2_3","DOIUrl":"https://doi.org/10.1007/978-3-031-34048-2_3","url":null,"abstract":"","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"32 1","pages":"29-40"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75504741","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}
Fergus Shone, N. Ravikumar, T. Lassila, Michael MacRaild, Yongxing Wang, Z. Taylor, P. Jimack, E. D. Armellina, Alejandro F Frangi
{"title":"Deep Physics-Informed Super-Resolution of Cardiac 4D-Flow MRI","authors":"Fergus Shone, N. Ravikumar, T. Lassila, Michael MacRaild, Yongxing Wang, Z. Taylor, P. Jimack, E. D. Armellina, Alejandro F Frangi","doi":"10.1007/978-3-031-34048-2_39","DOIUrl":"https://doi.org/10.1007/978-3-031-34048-2_39","url":null,"abstract":"","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"34 1","pages":"511-522"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84007690","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}
Taiyo Hasegawa, Helena Arvidsson, N. Tudzarovski, K. Meinke, R. Sugars, A. Nair
{"title":"Edge-Based Graph Neural Networks for Cell-Graph Modeling and Prediction","authors":"Taiyo Hasegawa, Helena Arvidsson, N. Tudzarovski, K. Meinke, R. Sugars, A. Nair","doi":"10.1007/978-3-031-34048-2_21","DOIUrl":"https://doi.org/10.1007/978-3-031-34048-2_21","url":null,"abstract":"","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"1 1","pages":"265-277"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89766452","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}
Wenqi Huang, Hongwei Li, G. Cruz, Jia-Yu Pan, D. Rueckert, K. Hammernik
{"title":"Neural Implicit k-Space for Binning-free Non-Cartesian Cardiac MR Imaging","authors":"Wenqi Huang, Hongwei Li, G. Cruz, Jia-Yu Pan, D. Rueckert, K. Hammernik","doi":"10.48550/arXiv.2212.08479","DOIUrl":"https://doi.org/10.48550/arXiv.2212.08479","url":null,"abstract":"In this work, we propose a novel image reconstruction framework that directly learns a neural implicit representation in k-space for ECG-triggered non-Cartesian Cardiac Magnetic Resonance Imaging (CMR). While existing methods bin acquired data from neighboring time points to reconstruct one phase of the cardiac motion, our framework allows for a continuous, binning-free, and subject-specific k-space representation.We assign a unique coordinate that consists of time, coil index, and frequency domain location to each sampled k-space point. We then learn the subject-specific mapping from these unique coordinates to k-space intensities using a multi-layer perceptron with frequency domain regularization. During inference, we obtain a complete k-space for Cartesian coordinates and an arbitrary temporal resolution. A simple inverse Fourier transform recovers the image, eliminating the need for density compensation and costly non-uniform Fourier transforms for non-Cartesian data. This novel imaging framework was tested on 42 radially sampled datasets from 6 subjects. The proposed method outperforms other techniques qualitatively and quantitatively using data from four and one heartbeat(s) and 30 cardiac phases. Our results for one heartbeat reconstruction of 50 cardiac phases show improved artifact removal and spatio-temporal resolution, leveraging the potential for real-time CMR.","PeriodicalId":73379,"journal":{"name":"Information processing in medical imaging : proceedings of the ... conference","volume":"59 1","pages":"548-560"},"PeriodicalIF":0.0,"publicationDate":"2022-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85622232","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}