Dhal, Krishna Gopal Ray, Swarnajit Rai, Rebika Das, Arunita
Published in
Archives of computational methods in engineering : state of the art reviews
The intricacy of the real-world numerical optimization tribulations has full-fledged and diversely amplified necessitating proficient yet ingenious optimization algorithms. In the domain wherein the classical approaches fall short, the predicament resolving nature-inspired optimization algorithms (NIOA) tend to hit upon an excellent solution to unb...
Emam, Marwa M Houssein, Essam H Ghoniem, Rania M
Published in
Computers in biology and medicine
In this paper, we proposed an enhanced reptile search algorithm (RSA) for global optimization and selected optimal thresholding values for multilevel image segmentation. RSA is a recent metaheuristic optimization algorithm depending on the hunting behavior of crocodiles. RSA is inclined to inadequate diversity, local optima, and unbalanced exploita...
Niu, Ke Guo, Zhongmin Peng, Xueping Pei, Su
Published in
Computers in biology and medicine
Brain tissue of Magnetic Resonance Imaging is precisely segmented and quantified, which aids in the diagnosis of neurological diseases such as epilepsy, Alzheimer's, and multiple sclerosis. Recently, UNet-like architectures are widely used for medical image segmentation, which achieved promising performance by using the skip connection to fuse the ...
Ma, Xin Zhao, Yajing Lu, Yiping Li, Peng Li, Xuanxuan Mei, Nan Wang, Jiajun Geng, Daoying Zhao, Lingxiao Yin, Bo
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Published in
Computers in biology and medicine
Treatment for meningiomas usually includes surgical removal, radiation therapy, and chemotherapy. Accurate segmentation of tumors significantly facilitates complete surgical resection and precise radiotherapy, thereby improving patient survival. In this paper, a deep learning model is constructed for magnetic resonance T1-weighted Contrast Enhancem...
Amyar, Amine Modzelewski, Romain Vera, Pierre Morard, Vincent Ruan, Su
Published in
Computers in biology and medicine
Predicting patient response to treatment and survival in oncology is a prominent way towards precision medicine. To this end, radiomics has been proposed as a field of study where images are used instead of invasive methods. The first step in radiomic analysis in oncology is lesion segmentation. However, this task is time consuming and can be physi...
Zhou, Haiying Bai, Qi Hu, Xianliang Alhaskawi, Ahmad Dong, Yanzhao Wang, Zewei Qi, Binjie Fang, Jianyong Kota, Vishnu Goutham Abdulla, Mohamed Hasan Abdulla Hasa
...
Published in
Journal of digital imaging
Carpal tunnel syndrome (CTS) is a common peripheral nerve disease in adults; it can cause pain, numbness, and even muscle atrophy and will adversely affect patients' daily life and work. There are no standard diagnostic criteria that go against the early diagnosis and treatment of patients. MRI as a novel imaging technique can show the patient's co...
Al Khalil, Yasmina Amirrajab, Sina Lorenz, Cristian Weese, Jürgen Pluim, Josien Breeuwer, Marcel
Published in
Medical image analysis
Deep learning-based segmentation methods provide an effective and automated way for assessing the structure and function of the heart in cardiac magnetic resonance (CMR) images. However, despite their state-of-the-art performance on images acquired from the same source (same scanner or scanner vendor) as images used during training, their performan...
Liu, Zewen
To study how axon growth is affected by the local environment biologists perform extensive experiments, watching the axons develop on different substrates. As axons grow from the neuron cell body they form tree-like structures, with branches forming and withering as they explore their surroundings. In this project, we designed a system which can tr...
Wodzinski, Marek Daniol, Mateusz Socha, Miroslaw Hemmerling, Daria Stanuch, Maciej Skalski, Andrzej
Published in
Computer methods and programs in biomedicine
This article presents a robust, fast, and fully automatic method for personalized cranial defect reconstruction and implant modeling. We propose a two-step deep learning-based method using a modified U-Net architecture to perform the defect reconstruction, and a dedicated iterative procedure to improve the implant geometry, followed by an automatic...
Yoo, Hye Jin Kim, Young Jae Hong, Hyunsook Hong, Sung Hwan Chae, Hee Dong Choi, Ja-Young
Published in
European radiology
To compare volumetric CT with DL-based fully automated segmentation and dual-energy X-ray absorptiometry (DXA) in the measurement of thigh tissue composition. This prospective study was performed from January 2019 to December 2020. The participants underwent DXA to determine the body composition of the whole body and thigh. CT was performed in the ...
