Special Issue on “Machine Learning/Deep Learning in Medical Image Processing”
Source abstract
Abstract
Many recent studies on medical image processing have involved the use of machine learning (ML) and deep learning (DL) [...]
Only a short abstract or summary was supplied by the source.
Source: crossref · Quality: short
Research context
OpenAlex topics: AI in cancer detection · Radiomics and Machine Learning in Medical Imaging · COVID-19 diagnosis using AI
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, 54 Kawahara-cho, Shogoin, Sakyo-ku, Kyoto 606-8507, Japan
Funding
Japan Society for the Promotion of Science
References (12)
Show source-provided references
1. Convolutional neural networks: An overview and application in radiology10.1007/s13244-018-0639-9 ↗
2. Deep Learning: A Primer for Radiologists10.1148/rg.2017170077 ↗
3. ImageNet Large Scale Visual Recognition Challenge10.1007/s11263-015-0816-y ↗
4. Nishio, M., Noguchi, S., and Fujimoto, K. (2020). Automatic Pancreas Segmentation Using Coarse-Scaled 2D Model of Deep Learning: Usefulness of Data Augmentation and Deep U-Net. Appl. Sci., 10.10.3390/app10103360 ↗
5. Urase, Y., Nishio, M., Ueno, Y., Kono, A., Sofue, K., Kanda, T., Maeda, T., Nogami, M., Hori, M., and Murakami, T. (2020). Simulation Study of Low-Dose Sparse-Sampling CT with Deep Learning-Based Reconstruction: Usefulness for Evaluation of Ovarian Cancer Metastasis. Appl. Sci., 10.10.3390/app10134446 ↗
6. Bhattacharjee, S., Kim, C.H., Prakash, D., Park, H.G., Cho, N.H., and Choi, H.K. (2020). An Efficient Lightweight CNN and Ensemble Machine Learning Classification of Prostate Tissue Using Multilevel Feature Analysis. Appl. Sci., 10.10.3390/app10228013 ↗
7. Martino, F., Bloisi, D.D., Pennisi, A., Fawakherji, M., Ilardi, G., Russo, D., Nardi, D., Staibano, S., and Merolla, F. (2020). Deep Learning-Based Pixel-Wise Lesion Segmentation on Oral Squamous Cell Carcinoma Images. Appl. Sci., 10.10.3390/app10228285 ↗
8. Saratxaga, C., Bote, J., Ortega-Morán, J., Picón, A., Terradillos, E., del Río, N., Andraka, N., Garrote, E., and Conde, O. (2021). Characterization of Optical Coherence Tomography Images for Colon Lesion Differentiation under Deep Learning. Appl. Sci., 11.10.3390/app11073119 ↗
9. Park, J., Hwang, J., Ryu, J., Nam, I., Kim, S.-A., Cho, B.-H., Shin, S.-H., and Lee, J.-Y. (2021). Deep Learning Based Airway Segmentation Using Key Point Prediction. Appl. Sci., 11.10.3390/app11083501 ↗
10. Papandrianos, N., and Papageorgiou, E. (2021). Automatic Diagnosis of Coronary Artery Disease in SPECT Myocardial Perfusion Imaging Employing Deep Learning. Appl. Sci., 11.10.3390/app11146362 ↗
11. (2021, December 03). ORCA Dataset. Available online: https://sites.google.com/unibas.it/orca.
12. (2021, December 03). The Cancer Genome Atlas Program—National Cancer Institute, Available online: https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga.