Lars J. Grimm
Orcid: 0000-0002-3865-3352
According to our database1,
Lars J. Grimm
authored at least 24 papers
between 2016 and 2023.
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Bibliography
2023
IEEE Trans. Medical Imaging, October, 2023
A user interface to communicate interpretable AI decisions to radiologists (Erratum).
Proceedings of the Medical Imaging 2023: Image Perception, 2023
Proceedings of the Medical Imaging 2023: Image Perception, 2023
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
2022
IEEE Trans. Biomed. Eng., 2022
2021
Retina-Match: Ipsilateral Mammography Lesion Matching in a Single Shot Detection Pipeline.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
2020
Prediction of Upstaged Ductal Carcinoma In Situ Using Forced Labeling and Domain Adaptation.
IEEE Trans. Biomed. Eng., 2020
Microcalcification localization and cluster detection using unsupervised convolutional autoencoders and structural similarity index.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
A multitask deep learning method in simultaneously predicting occult invasive disease in ductal carcinoma in-situ and segmenting microcalcifications in mammography.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2019
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ.
Comput. Biol. Medicine, 2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Synthesis and texture manipulation of screening mammograms using conditional generative adversarial network.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
Malignant microcalcification clusters detection using unsupervised deep autoencoders.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, 2019
2018
Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: a large scale evaluation.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
Improving classification with forced labeling of other related classes: application to prediction of upstaged ductal carcinoma in situ using mammographic features.
Proceedings of the Medical Imaging 2018: Computer-Aided Diagnosis, 2018
2017
Can upstaging of ductal carcinoma in situ be predicted at biopsy by histologic and mammographic features?
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
Prediction of occult invasive disease in ductal carcinoma in situ using computer-extracted mammographic features.
Proceedings of the Medical Imaging 2017: Computer-Aided Diagnosis, 2017
2016
Predicting false negative errors in digital breast tomosynthesis among radiology trainees using a computer vision-based approach.
Expert Syst. Appl., 2016
A computer vision-based algorithm to predict false positive errors in radiology trainees when interpreting digital breast tomosynthesis cases.
Expert Syst. Appl., 2016
Identification of error making patterns in lesion detection on digital breast tomosynthesis using computer-extracted image features.
Proceedings of the Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, San Diego, California, United States, 27 February, 2016