Automated registration method to correspond control point pairs with subpixel accuracy

1997 ◽  
Author(s):  
Hiroshi Hanaizumi ◽  
Yoshie Kinugawa ◽  
Sadao Fujimura
Keyword(s):  
Control Point ◽  
Registration Method ◽  
Subpixel Accuracy ◽  
Automated Registration

scholarly journals Tensor Image Registration Library: Automated Non-Linear Registration of Sparsely Sampled Histological Specimens to Post-Mortem MRI of the Whole Human Brain

2019 ◽  
Author(s):  
Istvan N. Huszar ◽  
Menuka Pallebage-Gamarallage ◽  
Sean Foxley ◽  
Benjamin C. Tendler ◽  
Anna Leonte ◽  
...  
Keyword(s):  
Image Registration ◽  
Human Brain ◽  
Brain Mri ◽  
List Type ◽  
Post Mortem ◽  
Whole Brain ◽  
Registration Method ◽  
Volume Registration ◽  
Histological Images ◽  
Automated Registration

AbstractThere is a need to understand the histopathological basis of MRI signal characteristics in complex biological matter. Microstructural imaging holds promise for sensitive and specific indicators of the early stages of human neurodegeneration but requires validation against traditional histological markers before it can be reliably applied in the clinical setting. Validation relies on a precise and preferably automatic method to align MRI and histological images of the same tissue, which poses unique challenges compared to more conventional MRI-to-MRI registration.A customisable open-source platform, Tensor Image Registration Library (TIRL) is presented. Based on TIRL, a fully automated pipeline was implemented to align small stained histological images with dissection photographs of corresponding tissue blocks and coronal brain slices, and further with high-resolution (0.5 mm) whole-brain post-mortem MRI data. The pipeline performed three separate deformable registrations to achieve accurate mapping between whole-brain MRI and small-slide histology coordinates. The robustness and accuracy of the individual registration steps were evaluated using both simulated data and real-life images from 6 different anatomical locations of one post-mortem human brain.The automated registration method demonstrated sub-millimetre accuracy in all steps, robustness against tissue damage, and good reproducibility between experiments. The method also outperformed manual landmark-based slice-to-volume registration, also correcting for curvatures in the slicing plane. Due to the customisability of TIRL, the pipeline can be conveniently adapted for other research needs and is therefore suitable for the large-scale comparison of routinely collected histology and MRI data.HighlightsTIRL: new framework for prototyping bespoke image registration pipelinesPipeline for automated registration of small-slide histology to whole-brain MRISlice-to-volume registration accounting for through-plane deformationsNo need for serial histological sampling

scholarly journals Using IVIM Parameters to Differentiate Prostate Cancer and Contralateral Normal Tissue through Fusion of MRI Images with Whole-Mount Pathology Specimen Images by Control Point Registration Method

Diagnostics ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2340
Author(s):  
Cheng-Chun Lee ◽  
Kuang-Hsi Chang ◽  
Feng-Mao Chiu ◽  
Yen-Chuan Ou ◽  
Jen-I. Hwang ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Image Fusion ◽  
Normal Tissue ◽  
Control Point ◽  
Fusion Method ◽  
Registration Method ◽  
Whole Mount ◽  
Mri Scans ◽  
Pathology Specimen ◽  
Image Fusion Method

The intravoxel incoherent motion (IVIM) model may enhance the clinical value of multiparametric magnetic resonance imaging (mpMRI) in the detection of prostate cancer (PCa). However, while past IVIM modeling studies have shown promise, they have also reported inconsistent results and limitations, underscoring the need to further enhance the accuracy of IVIM modeling for PCa detection. Therefore, this study utilized the control point registration toolbox function in MATLAB to fuse T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) MRI images with whole-mount pathology specimen images in order to eliminate potential bias in IVIM calculations. Sixteen PCa patients underwent prostate MRI scans before undergoing radical prostatectomies. The image fusion method was then applied in calculating the patients’ IVIM parameters. Furthermore, MRI scans were also performed on 22 healthy young volunteers in order to evaluate the changes in IVIM parameters with aging. Among the full study cohort, the f parameter was significantly increased with age, while the D* parameter was significantly decreased. Among the PCa patients, the D and ADC parameters could differentiate PCa tissue from contralateral normal tissue, while the f and D* parameters could not. The presented image fusion method also provided improved precision when comparing regions of interest side by side. However, further studies with more standardized methods are needed to further clarify the benefits of the presented approach and the different IVIM parameters in PCa characterization.

A robust and accurate automated registration method for turbine blade precision metrology

2018 ◽  
Vol 97 (9-12) ◽  
pp. 3711-3721 ◽  
Author(s):  
Wantao He ◽  
Zhongwei Li ◽  
Yanyan Guo ◽  
Xu Cheng ◽  
Kai Zhong ◽  
...  
Keyword(s):  
Turbine Blade ◽  
Registration Method ◽  
Precision Metrology ◽  
Automated Registration

The dosimetric impact of manual adjustments following automated registration in prostate image-guided radiotherapy

2017 ◽  
Vol 17 (1) ◽  
pp. 29-36
Author(s):  
Mohamed Nazmy ElBeltagi ◽  
Dean Harper ◽  
Lisa Coleman
Keyword(s):  
Prostate Cancer ◽  
Cancer Patients ◽  
Target Volume ◽  
Absolute Difference ◽  
Registration Method ◽  
Image Guided Radiotherapy ◽  
Image Guided ◽  
Manual Adjustment ◽  
Significant Difference ◽  
Automated Registration

AbstractAimAlthough manual adjustment of automatic cone beam computed tomography (CBCT) matching may improve the target coverage in certain points of interest, concerns exist that this may lead to dosimetric uncertainties which would negate the theoretical benefit of this approach. The objective of this study is to evaluate the dosimetric impact of manual adjustments made after automatic bony registration on CBCT in prostate patients.MethodsA total of 50 CBCT datasets of ten high-risk prostate cancer patients were randomly chosen. Each CBCT dataset was registered three times. Method (A): Automatic registration, Method (M1): Manual adjustment carried out by two experienced radiation therapists, Method (M2): Manual adjustment carried out by different radiation therapists with varying levels of experience. The clinical target volume (CTV), planning target volume (PTV), the bladder and the rectum were subsequently contoured on each CBCT dataset by a radiation oncologist blinded to the registration methods. The absolute difference of various dosimetric parameters were then analysed and compared with the original planning doses. A comparison of the three matching methods employed was also carried out.ResultsThere was a statistically significant difference in the magnitude of move taken in the inferior superior direction between M1 and M2 method. There were no significant differences observed in any of the dosimetric parameters examined in relation to the rectum, bladder or CTV. The only significant difference observed was the volume of PTV covered by the prescription isodose (95%) which was statistically significant lower in method A compared with both M1 and M2. There was no difference observed between M1 and M2 methods. The mean duration of the automated registration and subsequent analysis was 64 seconds compared with 91 seconds for automated registrations which included the additional manual adjustment.FindingsCBCT-based manual adjustments of automated bony-based registrations during the image-guided radiotherapy verification of prostate cancer patients can improve PTV coverage without impacting negatively on the doses received by the organs at risk. This strategy is associated with a small increase in overall treatment time.

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