Genggeng Qin
Orcid: 0000-0002-7563-3924
According to our database1,
Genggeng Qin
authored at least 17 papers
between 2017 and 2024.
Collaborative distances:
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Bibliography
2024
Deep-AutoMO: Deep automated multiobjective neural network for trustworthy lesion malignancy diagnosis in the early stage via digital breast tomosynthesis.
Comput. Biol. Medicine, 2024
2023
Bone suppression of lateral chest x-rays with imperfect and limited dual-energy subtraction images.
Comput. Medical Imaging Graph., April, 2023
2022
Lesion-specific exposure parameters for breast cancer diagnosis on digital breast tomosynthesis and full-field digital mammography.
Biomed. Signal Process. Control., 2022
2021
Synthesis of Mammogram From Digital Breast Tomosynthesis Using Deep Convolutional Neural Network With Gradient Guided cGANs.
IEEE Trans. Medical Imaging, 2021
Multi-criterion decision making-based multi-channel hierarchical fusion of digital breast tomosynthesis and digital mammography for breast mass discrimination.
Knowl. Based Syst., 2021
View Identification Assisted Fully Convolutional Network for Lung Field Segmentation of Frontal and Lateral Chest Radiographs.
IEEE Access, 2021
Improving Tuberculosis Recognition on Bone-Suppressed Chest X-Rays Guided by Task-Specific Features.
Proceedings of the Predictive Intelligence in Medicine - 4th International Workshop, 2021
Architectural distortion detection in digital breast tomosynthesis with adaptive receptive field and adaptive convolution kernel shape.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
2020
Multi-Objective-Based Radiomic Feature Selection for Lesion Malignancy Classification.
IEEE J. Biomed. Health Informatics, 2020
Generating Dual-Energy Subtraction Soft-Tissue Images from Chest Radiographs via Bone Edge-Guided GAN.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2019
Matching Corresponding Regions of Interest on Cranio-Caudal and Medio-Lateral Oblique View Mammograms.
IEEE Access, 2019
Bone Suppression of Chest Radiographs With Cascaded Convolutional Networks in Wavelet Domain.
IEEE Access, 2019
A shell and kernel descriptor based joint deep learning model for predicting breast lesion malignancy.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
2018
A fully automatic microcalcification detection approach based on deep convolution neural network.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Cascade of multi-scale convolutional neural networks for bone suppression of chest radiographs in gradient domain.
Medical Image Anal., 2017
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017