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Multi-View Information Fusion Using Multi-View Variational Autoencoder To Predict Proximal Femoral Fracture Load, Chen Zhao, Joyce H. Keyak, Xuewei Cao, Qiuying Sha, Li Wu, Zhe Luo, Lan Juan Zhao, Qing Tian, Michael Serou, Chuan Qiu, Kuan Jui Su, Hui Shen, Hong Wen Deng, Weihua Zhou
Multi-View Information Fusion Using Multi-View Variational Autoencoder To Predict Proximal Femoral Fracture Load, Chen Zhao, Joyce H. Keyak, Xuewei Cao, Qiuying Sha, Li Wu, Zhe Luo, Lan Juan Zhao, Qing Tian, Michael Serou, Chuan Qiu, Kuan Jui Su, Hui Shen, Hong Wen Deng, Weihua Zhou
Michigan Tech Publications, Part 2
Background: Hip fracture occurs when an applied force exceeds the force that the proximal femur can support (the fracture load or “strength”) and can have devastating consequences with poor functional outcomes. Proximal femoral strengths for specific loading conditions can be computed by subject-specific finite element analysis (FEA) using quantitative computerized tomography (QCT) images. However, the radiation and availability of QCT limit its clinical usability. Alternative low-dose and widely available measurements, such as dual energy X-ray absorptiometry (DXA) and genetic factors, would be preferable for bone strength assessment. The aim of this paper is to design a deep learning-based model to …
Experimental Study: Deep Learning-Based Fall Monitoring Among Older Adults With Skin-Wearable Electronics, Yongkuk Lee, Suresh Pokharel, Asra Al Muslim, Dukka Kc, Kyoung Hag Lee, Woon Hong Yeo
Experimental Study: Deep Learning-Based Fall Monitoring Among Older Adults With Skin-Wearable Electronics, Yongkuk Lee, Suresh Pokharel, Asra Al Muslim, Dukka Kc, Kyoung Hag Lee, Woon Hong Yeo
Michigan Tech Publications
Older adults are more vulnerable to falling due to normal changes due to aging, and their falls are a serious medical risk with high healthcare and societal costs. However, there is a lack of automatic fall detection systems for older adults. This paper reports (1) a wireless, flexible, skin-wearable electronic device for both accurate motion sensing and user comfort, and (2) a deep learning-based classification algorithm for reliable fall detection of older adults. The cost-effective skin-wearable motion monitoring device is designed and fabricated using thin copper films. It includes a six-axis motion sensor and is directly laminated on the skin …
Plmsnosite: An Ensemble-Based Approach For Predicting Protein S-Nitrosylation Sites By Integrating Supervised Word Embedding And Embedding From Pre-Trained Protein Language Model, Pawel Pratyush, Suresh Pokharel, Hiroto Saigo, Dukka Kc
Plmsnosite: An Ensemble-Based Approach For Predicting Protein S-Nitrosylation Sites By Integrating Supervised Word Embedding And Embedding From Pre-Trained Protein Language Model, Pawel Pratyush, Suresh Pokharel, Hiroto Saigo, Dukka Kc
Michigan Tech Publications
Background: Protein S-nitrosylation (SNO) plays a key role in transferring nitric oxide-mediated signals in both animals and plants and has emerged as an important mechanism for regulating protein functions and cell signaling of all main classes of protein. It is involved in several biological processes including immune response, protein stability, transcription regulation, post translational regulation, DNA damage repair, redox regulation, and is an emerging paradigm of redox signaling for protection against oxidative stress. The development of robust computational tools to predict protein SNO sites would contribute to further interpretation of the pathological and physiological mechanisms of SNO. Results: Using an …
A Non-Reference Evaluation Of Underwater Image Enhancement Methods Using A New Underwater Image Dataset, Ashraf Saleem, Sidike Paheding, Nathir Rawashdeh, Ali Awad, Navjot Kaur
A Non-Reference Evaluation Of Underwater Image Enhancement Methods Using A New Underwater Image Dataset, Ashraf Saleem, Sidike Paheding, Nathir Rawashdeh, Ali Awad, Navjot Kaur
Michigan Tech Publications
The rise of vision-based environmental, marine, and oceanic exploration research highlights the need for supporting underwater image enhancement techniques to help mitigate water effects on images such as blurriness, low color contrast, and poor quality. This paper presents an evaluation of common underwater image enhancement techniques using a new underwater image dataset. The collected dataset is comprised of 100 images of aquatic plants taken at a shallow depth of up to three meters from three different locations in the Great Lake Superior, USA, via a Remotely Operated Vehicle (ROV) equipped with a high-definition RGB camera. In particular, we use our …
Deep Learning For Medical Image Segmentation Using Prior Knowledge And Topology, Chen Zhao
Deep Learning For Medical Image Segmentation Using Prior Knowledge And Topology, Chen Zhao
Dissertations, Master's Theses and Master's Reports
Image segmentation refers to the division of a digital image into distinct segments or groups of pixels/voxels. However, most of the existing deep learning approaches lack the utilization of prior knowledge, such as shape information, which could improve segmentation accuracy. In addition, conventional image segmentation frequently falls short in preserving intricate spatial details, motivating the innovation of strategies for multi-scaled feature integration. Furthermore, traditional image segmentation methods primarily concentrate on pixel-level or region-level analysis. However, given the inherent morphological similarities among various image objects, the significance of topology information surpasses that of pixel-level data in the realm of medical image …