[HTML][HTML] Medical deep learning—A systematic meta-review
Deep learning has remarkably impacted several different scientific disciplines over the last
few years. For example, in image processing and analysis, deep learning algorithms were …
few years. For example, in image processing and analysis, deep learning algorithms were …
Automatic segmentation of mandible from conventional methods to deep learning—a review
B Qiu, H van der Wel, J Kraeima, HH Glas… - Journal of personalized …, 2021 - mdpi.com
Medical imaging techniques, such as (cone beam) computed tomography and magnetic
resonance imaging, have proven to be a valuable component for oral and maxillofacial …
resonance imaging, have proven to be a valuable component for oral and maxillofacial …
Introducing Biomedisa as an open-source online platform for biomedical image segmentation
We present Biomedisa, a free and easy-to-use open-source online platform developed for
semi-automatic segmentation of large volumetric images. The segmentation is based on a …
semi-automatic segmentation of large volumetric images. The segmentation is based on a …
Accuracy and precision of mandible segmentation and its clinical implications: virtual reality, desktop screen and artificial intelligence
Objective 3D modeling is a major challenge in computer-assisted surgery (CAS). Manual
segmentation, as the gold standard, is tedious, time consuming, and particularly challenging …
segmentation, as the gold standard, is tedious, time consuming, and particularly challenging …
Fully automatic segmentation of craniomaxillofacial CT scans for computer-assisted orthognathic surgery planning using the nnU-Net framework
Objectives To evaluate the performance of the nnU-Net open-source deep learning
framework for automatic multi-task segmentation of craniomaxillofacial (CMF) structures in …
framework for automatic multi-task segmentation of craniomaxillofacial (CMF) structures in …
A review on multiplatform evaluations of semi-automatic open-source based image segmentation for cranio-maxillofacial surgery
J Wallner, M Schwaiger, K Hochegger… - Computer methods and …, 2019 - Elsevier
Background and objectives Computer-assisted technologies, such as image-based
segmentation, play an important role in the diagnosis and treatment support in cranio …
segmentation, play an important role in the diagnosis and treatment support in cranio …
Studierfenster: an open science cloud-based medical imaging analysis platform
Imaging modalities such as computed tomography (CT) and magnetic resonance imaging
(MRI) are widely used in diagnostics, clinical studies, and treatment planning. Automatic …
(MRI) are widely used in diagnostics, clinical studies, and treatment planning. Automatic …
Multi-scale feature pyramid fusion network for medical image segmentation
B Zhang, Y Wang, C Ding, Z Deng, L Li, Z Qin… - International Journal of …, 2023 - Springer
Purpose Medical image segmentation is the most widely used technique in diagnostic and
clinical research. However, accurate segmentation of target organs from blurred border …
clinical research. However, accurate segmentation of target organs from blurred border …
A simplified cluster model and a tool adapted for collaborative labeling of lung cancer CT scans
SP Morozov, VA Gombolevskiy, AB Elizarov… - Computer Methods and …, 2021 - Elsevier
Background and objective: Lung cancer is the most common type of cancer with a high
mortality rate. Early detection using medical imaging is critically important for the long-term …
mortality rate. Early detection using medical imaging is critically important for the long-term …
Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites
Clinician generated segmentation of tumor and healthy tissue regions of interest (ROIs) on
medical images is crucial for radiotherapy. However, interobserver segmentation variability …
medical images is crucial for radiotherapy. However, interobserver segmentation variability …