Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance equivalent to the model ...
Feb 27, 2018 · Our results show that the proposed method reduce the training time by a factor of 15, while maintaining the classification performance ...
Feb 27, 2018 · PDF | On Feb 27, 2018, Ashfaq Khokhar and others published Reduction in training time of a deep learning model in detection of lesions in CT ...
Reduction in training time of a deep learning model in detection of lesions in CT. Nazanin Makkinejada, Nima Tajbakhsha, Amin Zarshenasa, Ashfaq Khokharb ...
5 days ago · We present the first machine learning-based autonomous hyperspectral neutron computed tomography experiment performed at the Spallation ...
Reduced-Dose Deep Learning Reconstruction for Abdominal CT of ...
pubs.rsna.org › doi › radiol.211838
Jan 11, 2022 · Deep learning image reconstruction (DLIR) improved CT image quality at 65% radiation dose reduction while preserving detection of liver lesions ...
Deep learning in medical imaging and radiation therapy - PMC - NCBI
www.ncbi.nlm.nih.gov › PMC9560030
The goals of this review paper on deep learning (DL) in medical imaging and radiation therapy are to (a) summarize what has been achieved to date; ...
Mar 6, 2023 · Deep learning-based techniques have demonstrated very efficient results in COVID-19 classification, detection and segmentation. Thorax computed ...
This chapter presents deep learning based techniques for automated liver lesion analysis in computed tomography (CT) images.
Oct 6, 2021 · This review discusses strategies to enlarge the data sample, decrease the time burden of manual supervised labeling, adjust the neural network ...