| 1. |
- Funk, Eva, 1953-, et al.
(författare)
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Patient-initiated breath-holds in MRI : an alternative for reducing respiratory artifacts and improving image quality
- 2015
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Ingår i: Clinical imaging. - : Elsevier. - 0899-7071 .- 1873-4499. ; 39:4, s. 619-622
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: To investigate MRI image quality using two different breath-hold techniques.Materials and methods: Thirty patients remitted for MRI, 2D-dual gradient echo acquisition of the liver conducted two separate breath-hold acquisitions in randomized order, operator-instructed and patient-initiated. The images were reviewed by two radiologists.Results: There were no significant differences in image quality between the two breath-hold techniques either in overall image quality or respiratory motion artifacts. This assessment was equal and concordant for both radiologists.Conclusion: In terms of image quality, the patient self-initiated breath-hold was shown to be an equal alternative to conventional breath-hold imaging.
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| 2. |
- Thunberg, Per, 1968-, et al.
(författare)
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Noise distribution in SENSE- and GRAPPA-reconstructed images : a computer simulation study
- 2007
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Ingår i: Magnetic Resonance Imaging. - New York, USA : Elsevier. - 0730-725X .- 1873-5894. ; 25:7, s. 1089-1094
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Tidskriftsartikel (refereegranskat)abstract
- This work presents a descriptive study of noise distributions in images reconstructed according to the parallel imaging methods SENSE and GRAPPA. In the computer simulations, two different settings were used for describing an object. The first setting included a synthetic object and eight complex-valued coil sensitivities. In the second setting, a complex-valued in vitro object, composed of four individual coil images, was used. After adding noise and subsampling k-space for each coil image, reconstruction was performed according to SENSE, with and without regularization, and GRAPPA for different reduction factors. A set of images was created for three different reduction factors. Noise distributions were determined for each data set and compared with each other. The results of this study show that the noise distributions in SENSE- and GRAPPA-reconstructed images differ. The noise in images reconstructed according to GRAPPA has a more uniform spatial distribution compared with SENSE-reconstructed images, in which the noise varies regionally according to the geometry factor. The noise distribution in SENSE-reconstructed images using regularization showed a similar but lowered pattern of noise compared with images reconstructed according to SENSE without regularization.
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| 3. |
- Andersén, Christoffer, 1991-, et al.
(författare)
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Deep learning based digitisation of prostate brachytherapy needles in ultrasound images
- 2020
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Ingår i: Medical physics. - : Wiley-Blackwell Publishing Inc.. - 2473-4209 .- 0094-2405. ; 47:12, s. 6414-6420
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To develop, and evaluate the performance of, a deep learning based 3D convolutional neural network (CNN) artificial intelligence (AI) algorithm aimed at finding needles in ultrasound images used in prostate brachytherapy.METHODS: Transrectal ultrasound (TRUS) image volumes from 1102 treatments were used to create a clinical ground truth (CGT) including 24422 individual needles that had been manually digitised by medical physicists during brachytherapy procedures. A 3D CNN U-net with 128x128x128 TRUS image volumes as input was trained using 17215 needle examples. Predictions of voxels constituting a needle were combined to yield a 3D linear function describing the localisation of each needle in a TRUS volume. Manual and AI digitisations were compared in terms of the root-mean-square distance (RMSD) along each needle, expressed as median and interquartile range (IQR). The method was evaluated on a dataset including 7207 needle examples. A subgroup of the evaluation data set (n=188) was created, where the needles were digitised once more by a medical physicist (G1) trained in brachytherapy. The digitisation procedure was timed.RESULTS: The RMSD between the AI and CGT was 0.55 (IQR: 0.35-0.86) mm. In the smaller subset, the RMSD between AI and CGT was similar (0.52 [IQR: 0.33-0.79] mm) but significantly smaller (p<0.001) than the difference of 0.75 (IQR: 0.49-1.20) mm between AI and G1. The difference between CGT and G1 was 0.80 (IQR: 0.48-1.18) mm, implying that the AI performed as well as the CGT in relation to G1. The mean time needed for human digitisation was 10 min 11 sec, while the time needed for the AI was negligible.CONCLUSIONS: A 3D CNN can be trained to identify needles in TRUS images. The performance of the network was similar to that of a medical physicist trained in brachytherapy. Incorporating a CNN for needle identification can shorten brachytherapy treatment procedures substantially.
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| 4. |
- Andersén, Christoffer, 1991-, et al.
(författare)
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Presults for the aI-Brachy study : Utilizing deep learning for needle reconstruction in prostate brachytherapy
- 2019
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Konferensbidrag (refereegranskat)abstract
- Purpose To develop a deep neural network for automatic reconstruction of needles in ultrasound images depicting the prostate during brachytherapy treatment of prostate cancer.Methods Ultrasound tomographies of the prostate from 907 treatments were used to train the artificial intelligent (AI) algorithm. The image matrices were downsampled to 128x128x128 and were used as in-data when training the AI, a 27 layer convolutional neural network. The needles were identified manually by medical physicists using conventional software. These reconstructions were used as gold standard when training the algorithm. An additional set of examinations were used for validation where the needle reconstructions by the AI were compared to the manual reconstructions. The root mean square deviation (RMSD) of needle position, including the central part (70 slices) of the needle was measured in order to avoid influence from artefacts around the needle tip. The result was also evaluated through visual inspection (see image). The times spent for manual vs. AI reconstruction were compared.Results RMSD for manual vs. AI reconstruction is on average (n=170) 1.18±1.0mm, whereas the difference between two manual operators is 0.02±0.06mm, which suggests that the AI is inferior to manual operators. The visual inspection, however, shows AI to be very accurate in positioning the needles. Manual reconstruction took approximately 11.0 minutes, whereas the time for the trained AI is negligible in comparison. Worth noticing regarding RMSD calculations is that, due to limited image resolution, small values may be under-estimated, hence overestimating the difference between the reconstruction methods.Conclusions The study implies that an AI may reconstruct needles for brachytherapy treatments of prostate cancer. The larger deviations between AI algorithm and manual operators, compared to between human operators appears to disagree with the high accuracy of the visual evaluation. However, visually, manual needle reconstructions appear to deviate more from the ultrasound image than do the AI reconstructions. This discrepancy is mainly caused by manual reconstruction software assuming straight needles, unlike the AI. We conclude that AI gives the opportunity to save a substantial amount of treatment planning time, when the patient is anesthetised. Further studies are needed to determine whether different reconstruction methods impact treatment plans.
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| 5. |
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| 6. |
- Andersson, Karin M., 1989-, et al.
(författare)
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Evaluation of two commercial CT metal artifact reduction algorithms for use in proton radiotherapy treatment planning in the head and neck area
- 2018
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Ingår i: Medical physics (Lancaster). - : Wiley-Blackwell Publishing Inc.. - 0094-2405 .- 2473-4209. ; 45:10, s. 4329-4344
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: To evaluate two commercial CT metal artifact reduction (MAR) algorithms for use in proton treatment planning in the head and neck (H&N) area.METHODS: An anthropomorphic head phantom with removable metallic implants (dental fillings or neck implant) was CT-scanned to evaluate the O-MAR (Philips) and the iMAR (Siemens) algorithms. Reference images were acquired without any metallic implants in place. Water equivalent thickness (WET) was calculated for different path directions and compared between image sets. Images were also evaluated for use in proton treatment planning for parotid, tonsil, tongue base, and neck node targets. The beams were arranged so as to not traverse any metal prior to the target, enabling evaluation of the impact on dose calculation accuracy from artifacts surrounding the metal volume. Plans were compared based on γ analysis (1 mm distance-to-agreement/1% difference in local dose) and dose volume histogram metrics for targets and organs at risk (OARs). Visual grading evaluation of 30 dental implant patient MAR images was performed by three radiation oncologists.RESULTS: In the dental fillings images, ΔWET along a low-density streak was reduced from -17.0 to -4.3 mm with O-MAR and from -16.1 mm to -2.3 mm with iMAR, while for other directions the deviations were increased or approximately unchanged when the MAR algorithms were used. For the neck implant images, ΔWET was generally reduced with MAR but residual deviations remained (of up to -2.3 mm with O-MAR and of up to -1.5 mm with iMAR). The γ analysis comparing proton dose distributions for uncorrected/MAR plans and corresponding reference plans showed passing rates >98% of the voxels for all phantom plans. However, substantial dose differences were seen in areas of most severe artifacts (γ passing rates of down to 89% for some cases). MAR reduced the deviations in some cases, but not for all plans. For a single patient case dosimetrically evaluated, minor dose differences were seen between the uncorrected and MAR plans (γ passing rate approximately 97%). The visual grading of patient images showed that MAR significantly improved image quality (P < 0.001).CONCLUSIONS: O-MAR and iMAR significantly improved image quality in terms of anatomical visualization for target and OAR delineation in dental implant patient images. WET calculations along several directions, all outside the metallic regions, showed that both uncorrected and MAR images contained metal artifacts which could potentially lead to unacceptable errors in proton treatment planning. ΔWET was reduced by MAR in some areas, while increased or unchanged deviations were seen for other path directions. The proton treatment plans created for the phantom images showed overall acceptable dose distributions differences when compared to the reference cases, both for the uncorrected and MAR images. However, substantial dose distribution differences in the areas of most severe artifacts were seen for some plans, which were reduced by MAR in some cases but not all. In conclusion, MAR could be beneficial to use for proton treatment planning; however, case-by-case evaluations of the metal artifact-degraded images are always recommended.
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| 7. |
- Andersson, Karin M., 1989-, et al.
(författare)
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Impact of Metal Artifacts on Proton Therapy Treatment Planning Accuracy
- 2017
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Ingår i: 56th Annual Meeting of the Particle Therapy Cooperative Group (PTCOG) 8-13 May 2017. - : The Particle Therapy Cooperative Group. ; , s. 68-68
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Purpose: To evaluate for proton therapy treatment planning the feasibility of two commercial metal artifact reduction (MAR) algorithms in CT-imaging.Materials and Methods: A head phantom with removable dental fillings and a body phantom with a removable hip prosthesis were scanned to evaluate O-MAR (Philips) and iMAR (Siemens). Reference images (scans without metal) were acquired and subtracted from the uncorrected (no MAR) and MAR-images. CT number-differences were mapped to differences in stopping power ratios to water. In addition, proton treatment plans for a parotid, tonsil and prostate-target were optimized based on uncorrected and MAR images and recalculated on reference images. Beams were arranged to not traverse metal, enabling evaluation of metal artifact impact on target coverage.Results: MAR algorithms reduced the most extreme dental filling artifacts, but residual artifacts still remained. iMAR reduced hip prosthesis artifacts to large extent, while considerable artifacts still were present with O-MAR. For parotid and tonsil-plans, D98%to PTV was nearly intact in the reference recalculations for both uncorrected and MAR-based plans, with maximum-difference,0.3%. For uncorrected prostate plans, D98%decreased more than 4% in the reference recalculation. For the iMAR prostate plan, D98%was almost identical in the reference recalculation (97.5% versus 97.4%). A slight D98%-decrease was seen in the reference for the O-MAR based plan (96.8% versus 97.5%).Conclusion: Hip prosthesis artifacts reduced target coverage accuracy, but it was substantially improved with MAR algorithms. Dental filling artifacts were moderately reduced with MAR, but did not substantially affect target coverage
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| 8. |
- Andersson, Karin M., 1989-, et al.
(författare)
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Metal artefact reduction in CT imaging of hip prostheses-an evaluation of commercial techniques provided by four vendors
- 2015
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Ingår i: British Journal of Radiology. - : British Institute of Radiology. - 0007-1285 .- 1748-880X. ; 88:1052
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Tidskriftsartikel (refereegranskat)abstract
- Objective: The aim of this study was to evaluate commercial metal artefact reduction (MAR) techniques in X-ray CT imaging of hip prostheses.Methods: Monoenergetic reconstructions of dual-energy CT (DECT) data and several different MAR algorithms, combined with single-energy CT or DECT, were evaluated by imaging a bilateral hip prosthesis phantom. The MAR images were compared with uncorrected images based on CT number accuracy and noise in different regions of interest.Results: The three MAR algorithms studied implied a general noise reduction (up to 67%, 74% and 77%) and an improvement in CT number accuracy, both in regions close to the prostheses and between the two prostheses. The application of monoenergetic reconstruction, without any MAR algorithm, did not decrease the noise in the regions close to the prostheses to the same extent as did the MAR algorithms and even increased the noise in the region between the prostheses.Conclusion: The MAR algorithms evaluated generally improved CT number accuracy and substantially reduced the noise in the hip prostheses phantom images, both close to the prostheses and between the two prostheses. The study showed that the monoenergetic reconstructions evaluated did not sufficiently reduce the severe metal artefact caused by large orthopaedic implants.Advances in knowledge: This study evaluates several commercially available MAR techniques in CT imaging of large orthopaedic implants.
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| 9. |
- Andersson, Karin M., 1989-, et al.
(författare)
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Metal Artifacts in CT Imaging of Hip Prostheses : Evaluation of Metal Artifact Reduction Techniques Provided by Four Vendors
- 2015
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- PURPOSE: The aim of this study was to evaluate metal artifact reduction (MAR) techniques, provided by four vendors, in CT imaging of hip prostheses.METHOD AND MATERIALS: A water phantom containing hip prostheses mounted in calf bones was scanned with four CT scanners; Philips Ingenuity; Toshiba Aquilion ONE Vision edition; GE Discovery 750 HD and Siemens SOMATOM Definition Flash. An uncorrected (reference) image was obtained for every CT and compared with images acquired with the scanner specific MAR technique; either monoenergetic reconstruction of Dual Energy CT (DECT) data (GE and Siemens) or the use of a MAR algorithm software (Philips and Toshiba), or a combination of the two (GE). The MAR techniques were applied for varying tube voltage, kernel and reconstruction technique. The reference images were quantitatively compared to the MAR images by analyzing the noise and the CT number accuracy in region of interests (ROIs). Visual grading was performed by five radiologists based on ten image quality (IQ) criteria.RESULTS: The MAR algorithms implied a general noise reduction (by up to 77%) and improved IQ based on the majority of the visual grading criteria. The use of monoenergetic reconstructions of DECT data, without any MAR algorithm, did not decrease the noise in the ROIs to the same extent as the MAR algorithms (up to 41%) and did even increase the noise in one ROI. The visual grading evaluation showed that monoenergetic reconstructions in general degraded the IQ for one of the DECT scanners and improved the IQ for only a few of the criteria for the other DECT scanner.CONCLUSION: The quantitative analysis and the visual grading evaluation showed that the IQ was generally improved when the MAR algorithms were used. However, additional artifacts and degradation of the IQ were noted in some MAR image regions. The use of monoenergetic reconstruction was concluded to not reduce metal artifacts to the same extent as the MAR algorithms and to even degrade the IQ in several image regions.CLINICAL RELEVANCE/APPLICATION: This study points out advantages and potential risks of using MAR techniques in CT imaging of hip prostheses and will be useful for clinics when optimizing CT scan protocols and purchasing new CT systems.
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| 10. |
- Andersson, Karin M., 1989-, et al.
(författare)
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Visual grading evaluation of commercially available metal artefact reduction techniques in hip prosthesis computed tomography
- 2016
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Ingår i: British Journal of Radiology. - London, United Kingdom : British Institute of Radiology. - 0007-1285 .- 1748-880X. ; 89:1063
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Tidskriftsartikel (refereegranskat)abstract
- Objectives: To evaluate metal artefact reduction (MAR) techniques from four computed tomography (CT) vendors in hip prosthesis imaging.Methods: Bilateral hip prosthesis phantom images, obtained by using MAR algorithms for single energy CT data or dual energy CT (DECT) data and by monoenergetic reconstructions of DECT data, were visually graded by five radiologists using ten image quality criteria. Comparisons between the MAR images and a reference image were performed for each scanner separately. Ordinal probit regression analysis was used.Results: The MAR algorithms in general improved the image quality based on the majority of the criteria (up to between 8/10 and 10/10) with a statistically improvement in overall image quality (P<0.001). However, degradation of image quality, such as new artefacts, was seen in some cases. A few monoenergetic reconstruction series improved the image quality (P<0.004) for one of the DECT scanners, but it was only improved for some of the criteria (up to 5/10). Monoenergetic reconstructions resulted in worse image quality for the majority of the criteria (up to 7/10) for the other DECT scanner.Conclusions: The MAR algorithms improved the image quality of the hip prosthesis CT images. However, since additional artefacts and degradation of image quality were seen in some cases, all algorithms should be carefully evaluated for every clinical situation. Monoenergetic reconstructions were in general concluded to be insufficient for reducing metal artifacts. Advances in knowledge: Qualitative evaluation of the usefulness of several MAR techniques from different vendors in CT imaging of hip prosthesis.
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