Roentgen: vision-language foundation model for chest x-ray generation
Multimodal models trained on large natural image-text pair datasets have exhibited
astounding abilities in generating high-quality images. Medical imaging data is …
astounding abilities in generating high-quality images. Medical imaging data is …
Image synthesis with disentangled attributes for chest X-ray nodule augmentation and detection
Lung nodule detection in chest X-ray (CXR) images is common to early screening of lung
cancers. Deep-learning-based Computer-Assisted Diagnosis (CAD) systems can support …
cancers. Deep-learning-based Computer-Assisted Diagnosis (CAD) systems can support …
Interpreting black box models via hypothesis testing
In science and medicine, model interpretations may be reported as discoveries of natural
phenomena or used to guide patient treatments. In such high-stakes tasks, false discoveries …
phenomena or used to guide patient treatments. In such high-stakes tasks, false discoveries …
[PDF][PDF] Deep learning inpainting model on digital and medical images-a review.
J Susan, P Subashini - Int. Arab J. Inf. Technol., 2023 - iajit.org
Image inpainting is a method to restore the missing pixels on damaged images. Initially, the
traditional inpainting method uses the statistics of the surrounding pixels to find the missing …
traditional inpainting method uses the statistics of the surrounding pixels to find the missing …
[PDF][PDF] Deep CMST framework for the autonomous recognition of heavily occluded and cluttered baggage items from multivendor security radiographs
Since the last two decades, luggage scanning has become one of the prime aviation
security concerns all over the world. Manual screening of the baggage items is a …
security concerns all over the world. Manual screening of the baggage items is a …
On the importance of domain awareness in classifier interpretations in medical imaging
Translating the success of deep learning-based computer-assisted classification into clinical
adaptation hinges on the ability to explain a prediction's causality. Post-hoc interpretability …
adaptation hinges on the ability to explain a prediction's causality. Post-hoc interpretability …
Deep learning‐based X‐ray inpainting for improving spinal 2D‐3D registration
H Esfandiari, S Weidert, I Kövesházi… - … Journal of Medical …, 2021 - Wiley Online Library
Abstract Background Two‐dimensional (2D)‐3D registration is challenging in the presence
of implant projections on intraoperative images, which can limit the registration capture …
of implant projections on intraoperative images, which can limit the registration capture …
See-through vision with unsupervised scene occlusion reconstruction
Among the greatest of the challenges of minimally invasive surgery (MIS) is the inadequate
visualisation of the surgical field through keyhole incisions. Moreover, occlusions caused by …
visualisation of the surgical field through keyhole incisions. Moreover, occlusions caused by …
sTBI-GAN: An adversarial learning approach for data synthesis on traumatic brain segmentation
Automatic brain segmentation of magnetic resonance images (MRIs) from severe traumatic
brain injury (sTBI) patients is critical for brain abnormality assessments and brain network …
brain injury (sTBI) patients is critical for brain abnormality assessments and brain network …
Cascaded structure tensor framework for robust identification of heavily occluded baggage items from multi-vendor X-ray scans
In the last two decades, luggage scanning has globally become one of the prime aviation
security concerns. Manual screening of the baggage items is a cumbersome, subjective and …
security concerns. Manual screening of the baggage items is a cumbersome, subjective and …