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SegMorph: Concurrent Motion Estimation and Segmentation for Cardiac MRI Sequences

IEEE Transactions on Medical Imaging 2024年 PP卷 1-1页

作者： Bi, Ning Zakeri, Arezoo Xia, Yan Cheng, Nina Taylor, Zeike A. Frangi, Alejandro F. Gooya, Ali University of Leeds Leeds UK Christabel Pankhurst Institute Division of Informatics Imaging and Data Sciences School of Health Sciences Faculty of Biology Medicine and Health University of Manchester Manchester UK CISTIB the School of Computing University of Leeds Leeds UK CISTIB School of Mechanical Engineering University of Leeds UK Christabel Pankhurst Institute Department of Computer Science Faculty of Science and Engineering and the Division of Informatics Imaging and Data Science Faculty of Biology Medicine and Health The University of Manchester Manchester UK School of Computing Science University of Glasgow Glasgow UK

We propose a novel recurrent variational network, SegMorph, to perform concurrent segmentation and motion estimation on cardiac cine magnetic resonance image (CMR) sequences. Our model establishes a recurrent latent space that captures spatiotemporal features from cine-MRI sequences for multitask inference and synthesis. The proposed model follows a recurrent variational auto-encoder framework and adopts a learnt prior from the temporal inputs. We utilise a multi-branch decoder to handle bi-ventricular segmentation and motion estimation simultaneously. In addition to the spatiotemporal features from the latent space, motion estimation enriches the supervision of sequential segmentation tasks by providing pseudo-ground truth. On the other hand, the segmentation branch helps with motion estimation by predicting deformation vector fields (DVFs) based on anatomical information. Experimental results demonstrate that the proposed method performs better than state-of-the-art approaches qualitatively and quantitatively for both segmentation and motion estimation tasks. We achieved an 81% average Dice Similarity Coefficient (DSC) and a less than 3.5 mm average Hausdorff distance on segmentation. Meanwhile, we achieved a motion estimation Dice Similarity Coefficient of over 79%, with approximately 0.14% of pixels displaying a negative Jacobian determinant in the estimated DVFs. IEEE

关键词： Motion estimation

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DRew: Dynamically Rewired Message Passing with Delay

arXiv

引用

arXiv 2023年

作者： Gutteridge, Benjamin Dong, Xiaowen Bronstein, Michael Di Giovanni, Francesco Department of Engineering Science University of Oxford United Kingdom Department of Computer Science University of Oxford United Kingdom Department of Computer Science and Technology University of Cambridge United Kingdom Faculty of Informatics University of Lugano Switzerland

Message passing neural networks (MPNNs) have been shown to suffer from the phenomenon of over-squashing that causes poor performance for tasks relying on long-range interactions. This can be largely attributed to message passing only occurring locally, over a node's immediate neighbours. Rewiring approaches attempting to make graphs 'more connected', and supposedly better suited to long-range tasks, often lose the inductive bias provided by distance on the graph since they make distant nodes communicate instantly at every layer. In this paper we propose a framework, applicable to any MPNN architecture, that performs a layer-dependent rewiring to ensure gradual densification of the graph. We also propose a delay mechanism that permits skip connections between nodes depending on the layer and their mutual distance. We validate our approach on several long-range tasks and show that it outperforms graph Transformers and multi-hop MPNNs. Copyright © 2023, The Authors. All rights reserved.

关键词： Message passing

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Smart Lighting System for Children's Therapy to Prevent Nyctophobia Syndrome at Bedtime 4

Smart Lighting System for Children's Therapy to Prevent Nyct...

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4th International Conference on Cybernetics and Intelligent System, ICORIS 2022

作者： Pramono, Andi Munir, Badrul Farchan, Muchammad Budiman, Satrio Arif Azis, Baskoro Putra, Wahyu Waskito Interior Design Department School of Design Bina Nusantara University Jakarta Indonesia Brawijaya University Departemen of Neurology Malang Indonesia Institut Teknologi Sepuluh Nopember Faculty of Intelligent Electrical and Informatics Technology Department of Electrical Engineering Surabaya Indonesia Brawijaya University Information System Computer Science Faculty Malang Indonesia

ISBN: (纸本)9781665453950

Everyone has a fundamental desire for sleep. By sleeping, humans can conserve energy and replenish their stamina to optimal levels. Lighting is one component that influences the quality of a person's sleep. One of them is a person who sleeps with the lights on, suffers from nyctophobia, has poor sleep quality, and may be responsible for several illnesses. This study aims to develop a smart lighting device that will aid in treating youngsters with nyctophobia to get used to sleeping with the lights off to improve their sleep quality. The case study methodology used in this study entails the development of a prototype. This method employs an oximeter as a heart rate detector and a sensor comparison as the measurement device. Arduino Uno circuit and heart rate sensor are the main devices in this research. At the same time, the NRF 24L01 is a communication medium between the two Arduino Uno boards. The experimental measurements in normal conditions indicate that the heart rate sensor was nearly the same as the value displayed by the oximeter. Similarly, after running for 1 minute, both devices produced almost identical results, with an average difference of 1 Beats Per Minute (BPM). According to experiments with a heart rate sensor, the switch-off condition can be activated if the heart rate hits 90 BPM. In this case, the light will switch off once the heart rate hits 70 BPM, which might be used for sleeping individuals. © 2022 IEEE.

关键词： Oximeters

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A Mobile App Game Based on the Development and Design of a Puzzle Created for Educational Learning 13th

A Mobile App Game Based on the Development and Design of a P...

引用

13th International Conference on Methodologies and Intelligent Systems for Technology Enhanced Learning, mis4TEL 2023

作者： Sapundzhi, Fatima Kitanov, Anton Lazarova, Meglena Georgiev, Slavi Department of Communication and Computer Engineering Faculty of Engineering South-West University "Neofit Rilski" 66 Ivan Myhailov Street Blagoevgrad2700 Bulgaria Faculty of Applied Mathematics and Informatics Technical University of Sofia 8 Kliment Ohridski Blvd. Sofia1000 Bulgaria Institute of Mathematics and Infromatics Bulgarian Academy of Sciences 8 Acad. Georgi Bonchev Street Sofia1113 Bulgaria Department of Applied Mathematics and Statistics University of Ruse "Angel Kanchev" 8 Studentska Street Ruse7004 Bulgaria

ISBN: (纸本)9783031421334

This paper presents a mobile app game designed for educational learning. The game is created by using contemporary software tools, featuring five different puzzle levels in which players have to solve jigsaw puzzles and eventually the player learns an interesting fact about the scene they arranged. The game aims to improve the young player’s spatial imagination, problem-solving skills, memory, patience, concentration and motor skills. In this study the steps how to develop and implement the game are thoroughly explained. The article highlights the importance of the educational games and their potential to enhance learning outcomes in a fun and engaging way. The game’s development process and design are discussed along with its potential to be utilized as an educational tool in various settings. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： E-learning

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WildGaussians: 3D Gaussian Splatting in the Wild

arXiv

引用

arXiv 2024年

作者： Kulhanek, Jonas Peng, Songyou Kukelova, Zuzana Pollefeys, Marc Sattler, Torsten Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Czech Republic Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Department of Computer Science ETH Zurich Switzerland Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

While the field of 3D scene reconstruction is dominated by NeRFs due to their photorealistic quality, 3D Gaussian Splatting (3DGS) has recently emerged, offering similar quality with real-time rendering speeds. However, both methods primarily excel with well-controlled 3D scenes, while in-the-wild data – characterized by occlusions, dynamic objects, and varying illumination – remains challenging. NeRFs can adapt to such conditions easily through per-image embedding vectors, but 3DGS struggles due to its explicit representation and lack of shared parameters. To address this, we introduce WildGaussians, a novel approach to handle occlusions and appearance changes with 3DGS. By leveraging robust DINO features and integrating an appearance modeling module within 3DGS, our method achieves state-of-the-art results. We demonstrate that WildGaussians matches the real-time rendering speed of 3DGS while surpassing both 3DGS and NeRF baselines in handling in-the-wild data, all within a simple architectural framework. Copyright © 2024, The Authors. All rights reserved.

关键词： 3D modeling

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Supply Chain Sustainability in Disruption: SC Intelligence, Customer Knowledge Transfer, and the Mediating Role of IS/IT

引用

IEEE engineering Management Review 2025年

作者： Ratna, Silvia Saide, Saide Rater, Salya Svyazhanovna, Baizakova Saule Herzavina, Herzavina Faculty of Information Technology Department of Informatics Engineering and Department of Information Systems Banjarmasin Indonesia State Islamic University of Sultan Syarif Kasim Riau Universitas Islam Negeri Sultan Syarif Kasim Riau-UIN SUSKA Riau Department of Information Systems Faculty of Science and Technology Indonesia PRO Knowledge Indonesia Pekanbaru Indonesia Universitas Pahlawan Tuanku Tambusai Indonesia Lembaga Enreach UIN Suska Riau Indonesia Politeknik Aceh Selatan Department of Informatics Engineering Aceh Indonesia Information Communication Technologies Robotics in Arkalyk Pedagogical Institute Master of Natural Sciences Educational Program for the Informatics Computer Science Kazakhstan Universitas Pahlawan Tuanku Tambusai Department of Informatics Engineering Indonesia National Taiwan University of Science and Technology Taiwan

Knowledge resource and information system/technology (IS/IT) capability have been considered to improve firm performance, however there is still a gap regarding the sustainability of supply chain to face and recover from disruption (e.g., COVID-19). Questionnaire-based surveys was adopted and received feedback from sixty (160) Indonesian companies or about 28.07% of response rate. © 1973-2011 IEEE.

关键词： customer knowledge transfer disruption information system/technology (IS/IT) responding knowledge management resource-based view (RBV) Supply chain (SC) sustainability supply chain knowledge transfer

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Diabetic Foot Ulcer Detection on Mobile Platforms through Thermal Imaging and Deep Learning

Diabetic Foot Ulcer Detection on Mobile Platforms through Th...

引用

International Conference on Smart Green Technology in Electrical and Information Systems (ICSGTEIS)

作者： Fitri Arnia Khairun Saddami Rusdha Muharar Dea Ananda Dwi Pratiwi Yudha Nurdin Department of Electrical and Computer Engineering Universitas Syiah Kuala Indonesia Telematics Research Center Universitas Syiah Kuala Indonesia Faculty of Mathematics and Informatics FernUniversität in Hagen Germany

Diabetes mellitus, causing substantial global mortality with millions affected in 2019, necessitates early detection methods to aid Diabetic Foot Ulcer (DFU) patients. We proposed a mobile application for early DFU identification using a Convolutional Neural Network (CNN) classifier. The application embedded a fine-tuned MobileNetV2 model specifically adapted for DFUs, trained on a plantar thermogram dataset through transfer learning. We evaluate the model’s classification performance pre- and post-embedded into the application. Results reveal that the pre-embedded model achieved 90% accuracy, 100% specificity, and 80% sensitivity. After embedding, the model retained 85% accuracy, 80% specificity, and 90% sensitivity. Notably, a slight accuracy decrease post-embedded is likely attributed to the normalization of the input image. This study emphasizes that the interplay between model performance and mobile embedded might influence the model’s performance. It underscores the meticulous consideration of mobile platform-specific processes crucial for accurate and effective early DFU detection.

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Spatial, Spatiotemporal, and Feature Analysis of Electroencephalogram During Imagined Speech with Visual vs Audio Cues

Spatial, Spatiotemporal, and Feature Analysis of Electroence...

引用

Electronic and Electrical engineering and Intelligent System (ICE3IS), International Conference on

作者： Nilam Fitriah Astri Budikayanti Hasballah Zakaria Tati Latifah Erawati Rajab Faculty of Computer Science Universitas Indonesia Depok Indonesia Department of Neurology Universitas Indonesia Jakarta Indonesia Department of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia

People with speech disorders have difficulties in social life and welfare. To overcome this barrier, researchers have conducted studies to recognize imagined speech from biosignals. The essential biosignals in producing speech are brain signals. This study aimed to determine activated brain regions during the imagined speech by spatial and spatiotemporal analysis to assist feature selection in imagined speech recognition. We recorded the normal subjects' brain signals using electroencephalography (EEG) when they imagined saying a word without vocalization. The protocol ran in two different-time sessions to cover the EEG nonstationary. We utilized visual cues in the first sub-session and audio cues in the second one. One word per sub-session had seven trials, each consisting of a rest state and cue presentation, followed by four repetitions of the imagined speech state, each preceded by a preparation state. We calculated power spectral entropy (PSE) values from the acquired dataset and used them as a feature since they captured signals' activity. The normalized PSE above 0.5 (middle value) was considered as high activity. The results showed that repeated-trial protocol induced brain activity during imagined speech. For visual or audio-cued imagined speech, the selected channels were in the central and left frontal regions, with additional right temporal, left parietal, and left occipital regions for visual-cued imagined speech. The highest PSE was found in the central region. Meanwhile, the lowest PSE was shown in the preparation state, confirming that cue presentation was not affecting imagined speech states.

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Solving the influence maximization problem by using entropy and weight of edges 12

Solving the influence maximization problem by using entropy ...

引用

12th International Conference on computer and Knowledge engineering, ICCKE 2022

作者： Kazemzadeh, Farzaneh Karian, Amir Mirzarezaee, Mitra Safaei, Ali Asghar Islamic Azad University Department of Computer Engineering Science and Research Branch Tehran Iran Islamic Azad University Central Tehran Branch Department of Industrial Design Iran Tarbiat Modares University Faculty of Medical Sciences Department of Medical Informatics Tehran Iran

ISBN: (数字)9781665476133

ISBN: (纸本)9781665476133

The Problem of Maximizing diffusion was raised to find the number of K nodes as a subset of all social network nodes. Many other social network nodes can be activated to get information by obtaining the right nodes in this set. Solving this problem optimally will improve and increase marketing and widely transfer any information on social networks. Although many studies have investigated this issue, there are a few studies on this algorithm for providing an optimal solution. Moreover, less attention has been paid to the difference between edges and their weights in society. Therefore, this study set a score appropriate to the conditions of each node according to the topological criteria and entropy, the level of communication, and the degree of neighbors around nodes. Then, K seeds with the highest influence was carefully identified according to the scores and their measurement. © 2022 IEEE.

关键词： Network topology

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Efficient Detection of Knee Osteoporosis Using the Swin Transformer on X-Ray Images

Efficient Detection of Knee Osteoporosis Using the Swin Tran...

引用

International Conference on computer and Applications (ICCA)

作者： Rahat Sultana Muhammad Zaman Nikola Ivković Korhan Cengiz Iqra Rafaqat Adnan Akhunzada Faculty of Computer Science The University of Lahore Sargodha Pakistan Department of Computer Science COMSATS University Islamabad Islamabad Pakistan Faculty of Organization and Informatics University of Zagreb Varaždin Croatia Department of E&E Engineering Biruni University Istanbul Turkey Department of Data and Cybersecurity University of Doha for Science and Technology Doha Qatar

ISBN: (数字)9798350367560

ISBN: (纸本)9798350367577

Knee Osteoporosis (KOP) is a skeletal disease that is caused by low bone mineral density and the degradation of bone tissue. It increases the risk of bone fractures in the knee region and is commonly seen in older people but usually ignored due to its silent nature. Osteoporosis is mostly diagnosed via X-ray images and Dual-Energy X-ray Absorptiometry (DXA) scans that can be difficult to read due to their sheer volume the subtle variations. This study aims to develop a Deep Learning (DL) utilizing Swin Transform model that can accurately recognize osteoporosis in knee X-ray images at an early stage. The dataset used for this research comprises knee X-rays labeled as either “normal” or “osteoporotic,” with image preprocessing including resizing to standard dimensions, converting the images into tensors, and normalizing pixel values to improve model performance. The model is trained and validated on arranged dataset, characterized by metrics such as accuracy, precision, recall or F1-score that gives an idea how well our model performs for prediction as acknowledged for its performance in image classification tasks. The results demonstrate that the Swin Transformer model has an overall accuracy of 89.38% on the data set for identifying osteoporosis features on knee X-ray images. This approach demonstrates the potential of the Swin Transformer model to serve as an effective tool for early osteoporosis diagnosis, offering improved accuracy and reliability compared to traditional convolutional neural networks (CNNs).

关键词： Deep learning Training Osteoporosis Accuracy Transforms Predictive models Transformers Feature extraction Data models X-ray imaging

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