LIVIVO - Search results -

Search results

Result 1 - 10 of total 94

Search options

Article ; Online: Improving chest X-ray report generation by leveraging warm starting.

Nicolson, Aaron / Dowling, Jason / Koopman, Bevan

2023 Volume 144, Page(s) 102633

Abstract: Automatically generating a report from a patient's Chest X-rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators-which are predominantly encoder-to-decoder models-lack the ... ...

Abstract	Automatically generating a report from a patient's Chest X-rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators-which are predominantly encoder-to-decoder models-lack the diagnostic accuracy to be deployed in a clinical setting. To improve CXR report generation, we investigate warm starting the encoder and decoder with recent open-source computer vision and natural language processing checkpoints, such as the Vision Transformer (ViT) and PubMedBERT. To this end, each checkpoint is evaluated on the MIMIC-CXR and IU X-ray datasets. Our experimental investigation demonstrates that the Convolutional vision Transformer (CvT) ImageNet-21K and the Distilled Generative Pre-trained Transformer 2 (DistilGPT2) checkpoints are best for warm starting the encoder and decoder, respectively. Compared to the state-of-the-art (M
MeSH term(s)	Humans ; X-Rays ; Natural Language Processing ; Workload
Language	English
Publishing date	2023-08-19
Publishing country	Netherlands
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	645179-2
ISSN	1873-2860 ; 0933-3657
ISSN (online)	1873-2860
ISSN	0933-3657
DOI	10.1016/j.artmed.2023.102633
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.A 2547: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (2.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Details ▾

Article ; Online: Automatic segmentation of tumour and organs at risk in 3D MRI for cervical cancer radiation therapy with anatomical variations.

Leung, Sze-Nung / Chandra, Shekhar S / Lim, Karen / Young, Tony / Holloway, Lois / Dowling, Jason A

Physical and engineering sciences in medicine

2024

Abstract: Cervical cancer is a common cancer in women globally, with treatment usually involving radiation therapy (RT). Accurate segmentation for the tumour site and organ-at-risks (OARs) could assist in the reduction of treatment side effects and improve ... ...

Abstract	Cervical cancer is a common cancer in women globally, with treatment usually involving radiation therapy (RT). Accurate segmentation for the tumour site and organ-at-risks (OARs) could assist in the reduction of treatment side effects and improve treatment planning efficiency. Cervical cancer Magnetic Resonance Imaging (MRI) segmentation is challenging due to a limited amount of training data available and large inter- and intra- patient shape variation for OARs. The proposed Masked-Net consists of a masked encoder within the 3D U-Net to account for the large shape variation within the dataset, with additional dilated layers added to improve segmentation performance. A new loss function was introduced to consider the bounding box loss during training with the proposed Masked-Net. Transfer learning from a male pelvis MRI data with a similar field of view was included. The approaches were compared to the 3D U-Net which was widely used in MRI image segmentation. The data used consisted of 52 volumes obtained from 23 patients with stage IB to IVB cervical cancer across a maximum of 7 weeks of RT with manually contoured labels including the bladder, cervix, gross tumour volume, uterus and rectum. The model was trained and tested with a 5-fold cross validation. Outcomes were evaluated based on the Dice Similarity Coefficients (DSC), the Hausdorff Distance (HD) and the Mean Surface Distance (MSD). The proposed method accounted for the small dataset, large variations in OAR shape and tumour sizes with an average DSC, HD and MSD for all anatomical structures of 0.790, 30.19mm and 3.15mm respectively.
Language	English
Publishing date	2024-04-24
Publishing country	Switzerland
Document type	Journal Article
ISSN	2662-4737
ISSN (online)	2662-4737
DOI	10.1007/s13246-024-01415-y
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: Longitudinal Data and a Semantic Similarity Reward for Chest X-Ray Report Generation

Nicolson, Aaron / Dowling, Jason / Koopman, Bevan

2023

Abstract: Chest X-Ray (CXR) report generation is a promising approach to improving the efficiency of CXR interpretation. However, a significant increase in diagnostic accuracy is required before that can be realised. Motivated by this, we propose a framework that ... ...

Abstract	Chest X-Ray (CXR) report generation is a promising approach to improving the efficiency of CXR interpretation. However, a significant increase in diagnostic accuracy is required before that can be realised. Motivated by this, we propose a framework that is more inline with a radiologist's workflow by considering longitudinal data. Here, the decoder is additionally conditioned on the report from the subject's previous imaging study via a prompt. We also propose a new reward for reinforcement learning based on CXR-BERT, which computes the similarity between reports. We conduct experiments on the MIMIC-CXR dataset. The results indicate that longitudinal data improves CXR report generation. CXR-BERT is also shown to be a promising alternative to the current state-of-the-art reward based on RadGraph. This investigation indicates that longitudinal CXR report generation can offer a substantial increase in diagnostic accuracy. Our Hugging Face model is available at: https://huggingface.co/aehrc/cxrmate and code is available at: https://github.com/aehrc/cxrmate.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	006
Publishing date	2023-07-19
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Prostate volume analysis in image registration for prostate cancer care: a verification study.

Bugeja, Jessica M / Mehawed, Georges / Roberts, Matthew J / Rukin, Nicholas / Dowling, Jason / Murray, Rebecca

Physical and engineering sciences in medicine

2023 Volume 46, Issue 4, Page(s) 1791–1802

Abstract: Combined magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) may enhance diagnosis, aid surgical planning and intra-operative orientation for prostate biopsy and radical prostatectomy. Although PET-MRI may ... ...

Abstract	Combined magnetic resonance imaging (MRI) and positron emission tomography/computed tomography (PET/CT) may enhance diagnosis, aid surgical planning and intra-operative orientation for prostate biopsy and radical prostatectomy. Although PET-MRI may provide these benefits, PET-MRI machines are not widely available. Image fusion of Prostate specific membrane antigen PET/CT and MRI acquired separately may be a suitable clinical alternative. This study compares CT-MR registration algorithms for urological prostate cancer care. Paired whole-pelvis MR and CT scan data were used (n = 20). A manual prostate CTV contour was performed independently on each patients MR and CT image. A semi-automated rigid-, automated rigid- and automated non-rigid registration technique was applied to align the MR and CT data. Dice Similarity Index (DSI), 95% Hausdorff distance (95%HD) and average surface distance (ASD) measures were used to assess the closeness of the manual and registered contours. The automated non-rigid approach had a significantly improved performance compared to the automated rigid- and semi-automated rigid-registration, having better average scores and decreased spread for the DSI, 95%HD and ASD (all p < 0.001). Additionally, the automated rigid approach had similar significantly improved performance compared to the semi-automated rigid registration across all accuracy metrics observed (all p < 0.001). Overall, all registration techniques studied here demonstrated sufficient accuracy for exploring their clinical use. While the fully automated non-rigid registration algorithm in the present study provided the most accurate registration, the semi-automated rigid registration is a quick, feasible, and accessible method to perform image registration for prostate cancer care by urologists and radiation oncologists now.
MeSH term(s)	Male ; Humans ; Prostate/diagnostic imaging ; Prostate/surgery ; Positron Emission Tomography Computed Tomography ; Tomography, X-Ray Computed/methods ; Prostatic Neoplasms/diagnostic imaging ; Prostatic Neoplasms/surgery ; Pelvis
Language	English
Publishing date	2023-10-11
Publishing country	Switzerland
Document type	Journal Article
ISSN	2662-4737
ISSN (online)	2662-4737
DOI	10.1007/s13246-023-01342-4
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Clinical validation of MR imaging time reduction for substitute/synthetic CT generation for prostate MRI-only treatment planning.

Young, Tony / Dowling, Jason / Rai, Robba / Liney, Gary / Greer, Peter / Thwaites, David / Holloway, Lois

Physical and engineering sciences in medicine

2023 Volume 46, Issue 3, Page(s) 1015–1021

Abstract: Radiotherapy treatment planning based only on magnetic resonance imaging (MRI) has become clinically achievable. Though computed tomography (CT) is the gold standard for radiotherapy imaging, directly providing the electron density values needed for ... ...

Abstract	Radiotherapy treatment planning based only on magnetic resonance imaging (MRI) has become clinically achievable. Though computed tomography (CT) is the gold standard for radiotherapy imaging, directly providing the electron density values needed for planning calculations, MRI has superior soft tissue visualisation to guide treatment planning decisions and optimisation. MRI-only planning removes the need for the CT scan, but requires generation of a substitute/synthetic/pseudo CT (sCT) for electron density information. Shortening the MRI imaging time would improve patient comfort and reduce the likelihood of motion artefacts. A volunteer study was previously carried out to investigate and optimise faster MRI sequences for a hybrid atlas-voxel conversion to sCT for prostate treatment planning. The aim of this follow-on study was to clinically validate the performance of the new optimised sequence for sCT generation in a treated MRI-only prostate patient cohort. 10 patients undergoing MRI-only treatment were scanned on a Siemens Skyra 3T MRI as part of the MRI-only sub-study of the NINJA clinical trial (ACTRN12618001806257). Two sequences were used, the standard 3D T2-weighted SPACE sequence used for sCT conversion which has been previously validated against CT, and a modified fast SPACE sequence, selected based on the volunteer study. Both were used to generate sCT scans. These were then compared to evaluate the fast sequence conversion for anatomical and dosimetric accuracy against the clinically approved treatment plans. The average Mean Absolute Error (MAE) for the body was 14.98 ± 2.35 HU, and for bone was 40.77 ± 5.51 HU. The external volume contour comparison produced a Dice Similarity Coefficient (DSC) of at least 0.976, and an average of 0.985 ± 0.004, and the bony anatomy contour comparison a DSC of at least 0.907, and an average of 0.950 ± 0.018. The fast SPACE sCT agreed with the gold standard sCT within an isocentre dose of -0.28% ± 0.16% and an average gamma pass rate of 99.66% ± 0.41% for a 1%/1 mm gamma tolerance. In this clinical validation study, the fast sequence, which reduced the required imaging time by approximately a factor of 4, produced an sCT with similar clinical dosimetric results compared to the standard sCT, demonstrating its potential for clinical use for treatment planning.
MeSH term(s)	Humans ; Male ; Magnetic Resonance Imaging/methods ; Pelvis ; Prostate ; Radiotherapy Planning, Computer-Assisted/methods ; Tomography, X-Ray Computed/methods
Language	English
Publishing date	2023-05-23
Publishing country	Switzerland
Document type	Clinical Trial ; Journal Article
ISSN	2662-4737
ISSN (online)	2662-4737
DOI	10.1007/s13246-023-01268-x
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Book ; Online: Improving Chest X-Ray Report Generation by Leveraging Warm Starting

Nicolson, Aaron / Dowling, Jason / Koopman, Bevan

2022

Abstract: Automatically generating a report from a patient's Chest X-Rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators -- which are predominantly encoder-to-decoder models -- lack ... ...

Abstract	Automatically generating a report from a patient's Chest X-Rays (CXRs) is a promising solution to reducing clinical workload and improving patient care. However, current CXR report generators -- which are predominantly encoder-to-decoder models -- lack the diagnostic accuracy to be deployed in a clinical setting. To improve CXR report generation, we investigate warm starting the encoder and decoder with recent open-source computer vision and natural language processing checkpoints, such as the Vision Transformer (ViT) and PubMedBERT. To this end, each checkpoint is evaluated on the MIMIC-CXR and IU X-Ray datasets. Our experimental investigation demonstrates that the Convolutional vision Transformer (CvT) ImageNet-21K and the Distilled Generative Pre-trained Transformer 2 (DistilGPT2) checkpoints are best for warm starting the encoder and decoder, respectively. Compared to the state-of-the-art ($\mathcal{M}^2$ Transformer Progressive), CvT2DistilGPT2 attained an improvement of 8.3\% for CE F-1, 1.8\% for BLEU-4, 1.6\% for ROUGE-L, and 1.0\% for METEOR. The reports generated by CvT2DistilGPT2 have a higher similarity to radiologist reports than previous approaches. This indicates that leveraging warm starting improves CXR report generation. Code and checkpoints for CvT2DistilGPT2 are available at https://github.com/aehrc/cvt2distilgpt2.
Keywords	Computer Science - Computer Vision and Pattern Recognition
Subject code	004
Publishing date	2022-01-23
Publishing country	us
Document type	Book ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Opportunities for image analysis in radiation oncology.

Dowling, Jason A

Australasian physical & engineering sciences in medicine

2014 Volume 37, Issue 2, Page(s) 275–277

MeSH term(s)	Diagnostic Imaging ; Humans ; Image Interpretation, Computer-Assisted ; Image Processing, Computer-Assisted ; Radiation Oncology
Language	English
Publishing date	2014-06
Publishing country	Netherlands
Document type	Editorial
ZDB-ID	46226-3
ISSN	1879-5447 ; 0158-9938
ISSN (online)	1879-5447
ISSN	0158-9938
DOI	10.1007/s13246-014-0278-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Zs.B 2684: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Deformable image registration in radiation therapy.

Dowling, Jason A / O'Connor, Laura M

Journal of medical radiation sciences

2020 Volume 67, Issue 4, Page(s) 257–259

Abstract: Deformable image registration is an increasingly important method to account for soft tissue deformation between image acquisitions. This editorial discusses the clinical need and current status of deformable image registration. ...

Abstract	Deformable image registration is an increasingly important method to account for soft tissue deformation between image acquisitions. This editorial discusses the clinical need and current status of deformable image registration.
MeSH term(s)	Algorithms ; Humans ; Image Processing, Computer-Assisted ; Phantoms, Imaging ; Radiotherapy Planning, Computer-Assisted
Language	English
Publishing date	2020-10-26
Publishing country	United States
Document type	Editorial
ZDB-ID	2734841-6
ISSN	2051-3909 ; 2051-3909
ISSN (online)	2051-3909
ISSN	2051-3909
DOI	10.1002/jmrs.446
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Determination of acceptable Hounsfield units uncertainties via a sensitivity analysis for an accurate dose calculation in the context of prostate MRI-only radiotherapy.

Chourak, Hilda / Barateau, Anaïs / Greer, Peter / Lafond, Caroline / Nunes, Jean-Claude / de Crevoisier, Renaud / Dowling, Jason / Acosta, Oscar

Physical and engineering sciences in medicine

2023 Volume 46, Issue 4, Page(s) 1703–1711

Abstract: Radiation therapy is moving from CT based to MRI guided planning, particularly for soft tissue anatomy. An important requirement of this new workflow is the generation of synthetic-CT (sCT) from MRI to enable treatment dose calculations. Automatic ... ...

Abstract	Radiation therapy is moving from CT based to MRI guided planning, particularly for soft tissue anatomy. An important requirement of this new workflow is the generation of synthetic-CT (sCT) from MRI to enable treatment dose calculations. Automatic methods to determine the acceptable range of CT Hounsfield Unit (HU) uncertainties to avoid dose distribution errors is thus a key step toward safe MRI-only radiotherapy. This work has analysed the effects of controlled errors introduced in CT scans on the delivered radiation dose for prostate cancer patients. Spearman correlation coefficient has been computed, and a global sensitivity analysis performed following the Morris screening method. This allows the classification of different error factors according to their impact on the dose at the isocentre. sCT HU estimation errors in the bladder appeared to be the least influential factor, and sCT quality assessment should not only focus on organs surrounding the radiation target, as errors in other soft tissue may significantly impact the dose in the target volume. This methodology links dose and intensity-based metrics, and is the first step to define a threshold of acceptability of HU uncertainties for accurate dose planning.
MeSH term(s)	Male ; Humans ; Prostate/diagnostic imaging ; Tomography, X-Ray Computed/methods ; Prostatic Neoplasms/diagnostic imaging ; Prostatic Neoplasms/radiotherapy ; Urinary Bladder ; Magnetic Resonance Imaging/methods
Language	English
Publishing date	2023-10-10
Publishing country	Switzerland
Document type	Journal Article
ISSN	2662-4737
ISSN (online)	2662-4737
DOI	10.1007/s13246-023-01333-5
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Evaluating the relationship between contouring variability and modelled treatment outcome for prostate bed radiotherapy.

Le Bao, Viet / Haworth, Annette / Dowling, Jason / Walker, Amy / Arumugam, Sankar / Jameson, Michael / Chlap, Phillip / Wiltshire, Kirsty / Keats, Sarah / Cloak, Kirrily / Sidhom, Mark / Kneebone, Andrew / Holloway, Lois

Physics in medicine and biology

2024 Volume 69, Issue 8

Abstract: Objectives. ...

Abstract	Objectives.
MeSH term(s)	Male ; Humans ; Prostate ; Prostatic Neoplasms/diagnostic imaging ; Prostatic Neoplasms/radiotherapy ; Prostatic Neoplasms/surgery ; Radiotherapy Planning, Computer-Assisted/methods ; Retrospective Studies ; Radiotherapy, Intensity-Modulated/methods ; Radiotherapy Dosage ; Treatment Outcome
Language	English
Publishing date	2024-04-03
Publishing country	England
Document type	Journal Article
ZDB-ID	208857-5
ISSN	1361-6560 ; 0031-9155
ISSN (online)	1361-6560
ISSN	0031-9155
DOI	10.1088/1361-6560/ad3325
Database	MEDical Literature Analysis and Retrieval System OnLINE

In stock of ZB MED Cologne/Königswinter

Zs.A 199: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
Jg. 1995 - 2021: Lesesall (1.OG)
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾
- See ZB MED holdings
- Order with fees

To top

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito