AI for Advanced Biomedical Applications
Scope
Artificial Intelligence (AI) is advancing biomedical science in many ways, from improving image-based diagnostics to engineering strategies for improving movement related to injury, birth defects, or neurological or cardiovascular disease, to predicting behavior and nerve responses to stimuli. BME Frontiers is assembling a special issue highlighting the latest applications of AI to biomedical science and invites you to submit your research for consideration.
The focus will be primarily on the application of AI to biomedical imaging, however, studies related to other biomedical applications of AI are welcome. If your research applies AI to any of these areas, we encourage you to submit:
- Learning-based algorithms for biological or medical imaging, including disease diagnosis and prognosis, improving image clarity or resolution, and enabling cross-modality comparison
- Automated approaches, such as computer vision, to localizing and tracking moving targets
- Image-guided therapy, including planning for and execution of surgical procedures and during surgical interventions
- Image-omics and radiomics in disease diagnosis and therapy, including quantitative approaches to molecular diagnostic and therapeutic imaging
- Discovery-based applications of AI in biomedicine
- Fusion of machine learning and domain knowledge, including feature extraction and computational modeling from biomedical images and annotation-efficient learning from biomedical imaging
- Biomedical image synthesis and editing
- Detection and segmentation from biomedical images
Guest Editors
Professor Rama Chellappa, Johns Hopkins University
Professor S. Kevin Zhou, University of Science and Technology of China
Professor Jeremy Walston, Johns Hopkins School of Medicine
Table of Contents
As articles within the special issue are published they will appear below.
Simulated MRI Artifacts: Testing Machine Learning Failure Modes
Nicholas C. Wang, Douglas C. Noll, Ashok Srinivasan, Johann Gagnon-Bartsch, Michelle M. Kim, Arvind Rao
BME Frontiers, vol. 2022, Article ID 9807590, 16 pages, 2022
Jointly Optimized Spatial Histogram UNET Architecture (JOSHUA) for Adipose Tissue Segmentation
Joshua K. Peeples, Julie F. Jameson, Nisha M. Kotta, Jonathan M. Grasman, Whitney L. Stoppel, Alina Zare
BME Frontiers, vol. 2022, Article ID 9854084, 14 pages, 2022
A Low-Cost High-Performance Data Augmentation for Deep Learning-Based Skin Lesion Classification
Shuwei Shen, Mengjuan Xu, Fan Zhang, Pengfei Shao, Honghong Liu, Liang Xu, Chi Zhang, Peng Liu, Zhihong Zhang, Peng Yao, Ronald X. Xu
BME Frontiers, vol. 2022, Article ID 9765307, 12 pages, 2022
Impedance Imaging of Cells and Tissues: Design and Applications
Raziyeh Bounik, Fernando Cardes, Hasan Ulusan, Mario M. Modena, Andreas Hierlemann
BME Frontiers, vol. 2022, Article ID 9857485, 21 pages, 2022
A Deep Learning Approach for Detecting Colorectal Cancer via Raman Spectra
Zheng Cao, Xiang Pan, Hongyun Yu, Shiyuan Hua, Da Wang, Danny Z. Chen, Min Zhou, Jian Wu
BME Frontiers, vol. 2022, Article ID 9872028, 10 pages, 2022
Alina Dubatovka, Joachim M. Buhmann
BME Frontiers, vol. 2022, Article ID 9813062, 12 pages, 2022
Deep Segmentation Feature-Based Radiomics Improves Recurrence Prediction of Hepatocellular Carcinoma
Jifei Wang, Dasheng Wu, Meili Sun, Zhenpeng Peng, Yingyu Lin, Hongxin Lin, Jiazhao Chen, Tingyu Long, Zi-Ping Li, Chuanmiao Xie, Bingsheng Huang, Shi-Ting Feng
BME Frontiers, vol. 2022, Article ID 9793716, 12 pages, 2022
Breast Cancer Induced Bone Osteolysis Prediction Using Temporal Variational Autoencoders
Wei Xiong, Neil Yeung, Shubo Wang, Haofu Liao, Liyun Wang, Jiebo Luo
BME Frontiers, vol. 2022, Article ID 9763284, 10 pages, 2022
Connectivity-based Cortical Parcellation via Contrastive Learning on Spatial-Graph Convolution
Peiting You, Xiang Li, Fan Zhang, Quanzheng Li
BME Frontiers, vol. 2022, Article ID 9814824, 11 pages, 2022
Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer with Deep Learning
Hailing Liu, Yu Zhao, Fan Yang, Xiaoying Lou, Feng Wu, Hang Li, Xiaohan Xing, Tingying Peng, Bjoern Menze, Junzhou Huang, Shujun Zhang, Anjia Han, Jianhua Yao, Xinjuan Fan
BME Frontiers, vol. 2022, Article ID 9860179, 12 pages, 2022
Weakly- and Semisupervised Probabilistic Segmentation and Quantification of Reverberation Artifacts
Alex Ling Yu Hung, Edward Chen, John Galeotti
BME Frontiers, vol. 2022, Article ID 9837076, 15 pages, 2022
A Review of Deep Learning Applications in Lung Ultrasound Imaging of COVID-19 Patients
Lingyi Zhao, Muyinatu A. Lediju Bell
BME Frontiers, vol. 2022, Article ID 9780173, 17 pages, 2022
Automated Segmentation and Connectivity Analysis for Normal Pressure Hydrocephalus
Angela Zhang, Amil Khan, Saisidharth Majeti, Judy Pham, Christopher Nguyen, Peter Tran, Vikram Iyer, Ashutosh Shelat, Jefferson Chen, B. S. Manjunath
BME Frontiers, vol. 2022, Article ID 9783128, 13 pages, 2022