Jacob L. Jaremko
Orcid: 0000-0001-5314-2297
According to our database1,
Jacob L. Jaremko
authored at least 43 papers
between 2016 and 2024.
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Bibliography
2024
A Simple Framework Uniting Visual In-context Learning with Masked Image Modeling to Improve Ultrasound Segmentation.
CoRR, 2024
CoRR, 2024
2023
Comput. Medical Imaging Graph., October, 2023
ACU2E-Net: A novel predict-refine attention network for segmentation of soft-tissue structures in ultrasound images.
Comput. Biol. Medicine, May, 2023
Unsupervised Multi-Latent Space RL Framework for Video Summarization in Ultrasound Imaging.
IEEE J. Biomed. Health Informatics, 2023
Self-supervised TransUNet for Ultrasound regional segmentation of the distal radius in children.
CoRR, 2023
Unsupervised landmark detection and classification of lung infection using transporter neural networks.
Comput. Biol. Medicine, 2023
Self-Supervised Learning to More Efficiently Generate Segmentation Masks for Wrist Ultrasound.
Proceedings of the Simplifying Medical Ultrasound - 4th International Workshop, 2023
2022
CoRR, 2022
Improved-Mask R-CNN: Towards an accurate generic MSK MRI instance segmentation platform (data from the Osteoarthritis Initiative).
Comput. Medical Imaging Graph., 2022
Comput. Biol. Medicine, 2022
Proceedings of the Simplifying Medical Ultrasound - Third International Workshop, 2022
Proceedings of the Pattern Recognition, Computer Vision, and Image Processing. ICPR 2022 International Workshops and Challenges, 2022
Proceedings of the Artificial Intelligence in Medicine, 2022
2021
Medical Biol. Eng. Comput., 2021
Physics Driven Domain Specific Transporter Framework with Attention Mechanism for Ultrasound Imaging.
CoRR, 2021
Unsupervised multi-latent space reinforcement learning framework for video summarization in ultrasound imaging.
CoRR, 2021
Learning the Imaging Landmarks: Unsupervised Key point Detection in Lung Ultrasound Videos.
CoRR, 2021
Sample Efficient Learning of Image-Based Diagnostic Classifiers Using Probabilistic Labels.
CoRR, 2021
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Thyroid Nodule Segmentation and Classification Using Deep Convolutional Neural Network and Rule-based Classifiers.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
MRI Knee Domain Translation for Unsupervised Segmentation By CycleGAN (data from Osteoarthritis initiative (OAI)).
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
Integrating User-Input into Deep Convolutional Neural Networks for Thyroid Nodule Segmentation.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
Sample efficient learning of image-based diagnostic classifiers via probabilistic labels.
Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
2020
Analysis of four methods of measuring three-dimensional pelvic tilt in the lateral decubitus position.
Medical Biol. Eng. Comput., 2020
Medical Biol. Eng. Comput., 2020
A systematic review on the role of artificial intelligence in sonographic diagnosis of thyroid cancer: Past, present and future.
CoRR, 2020
Automated thyroid nodule detection from ultrasound imaging using deep convolutional neural networks.
Comput. Biol. Medicine, 2020
Int. J. Comput. Assist. Radiol. Surg., 2020
2018
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Segmentation-by-detection: A cascade network for volumetric medical image segmentation.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
Proceedings of the 28th Annual International Conference on Computer Science and Software Engineering, 2018
2017
Dependent nonparametric bayesian group dictionary learning for online reconstruction of dynamic MR images.
Pattern Recognit., 2017
Multi-dimensional low rank plus sparse decomposition for reconstruction of under-sampled dynamic MRI.
Pattern Recognit., 2017
Semiautomatic classification of acetabular shape from three-dimensional ultrasound for diagnosis of infant hip dysplasia using geometric features.
Int. J. Comput. Assist. Radiol. Surg., 2017
Proceedings of the 14th IEEE International Symposium on Biomedical Imaging, 2017
2016
Toward automated classification of acetabular shape in ultrasound for diagnosis of DDH: Contour alpha angle and the rounding index.
Comput. Methods Programs Biomed., 2016
A technique for semiautomatic segmentation of echogenic structures in 3D ultrasound, applied to infant hip dysplasia.
Int. J. Comput. Assist. Radiol. Surg., 2016
Fully Automating Graf's Method for DDH Diagnosis Using Deep Convolutional Neural Networks.
Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016
Proceedings of the 2016 IEEE International Conference on Image Processing, 2016
Hip segmentation from MRI volumes in infants for DDH diagnosis and treatment planning.
Proceedings of the 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2016