scholarly journals Temporal subtraction CT with nonrigid image registration improves detection of bone metastases by radiologists: results of a large-scale observer study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Koji Onoue ◽  
Masahiro Yakami ◽  
Mizuho Nishio ◽  
Ryo Sakamoto ◽  
Gakuto Aoyama ◽  
...  
Keyword(s):  
Image Registration ◽  
Bone Metastases ◽  
Large Scale ◽  
Ct Images ◽  
Operating Characteristics ◽  
Nonrigid Image Registration ◽  
Temporal Subtraction ◽  
Significant Difference ◽  
Image Pairs ◽  
Mean Sensitivity

AbstractTo determine whether temporal subtraction (TS) CT obtained with non-rigid image registration improves detection of various bone metastases during serial clinical follow-up examinations by numerous radiologists. Six board-certified radiologists retrospectively scrutinized CT images for patients with history of malignancy sequentially. These radiologists selected 50 positive and 50 negative subjects with and without bone metastases, respectively. Furthermore, for each subject, they selected a pair of previous and current CT images satisfying predefined criteria by consensus. Previous images were non-rigidly transformed to match current images and subtracted from current images to automatically generate TS images. Subsequently, 18 radiologists independently interpreted the 100 CT image pairs to identify bone metastases, both without and with TS images, with each interpretation separated from the other by an interval of at least 30 days. Jackknife free-response receiver operating characteristics (JAFROC) analysis was conducted to assess observer performance. Compared with interpretation without TS images, interpretation with TS images was associated with a significantly higher mean figure of merit (0.710 vs. 0.658; JAFROC analysis, P = 0.0027). Mean sensitivity at lesion-based was significantly higher for interpretation with TS compared with that without TS (46.1% vs. 33.9%; P = 0.003). Mean false positive count per subject was also significantly higher for interpretation with TS than for that without TS (0.28 vs. 0.15; P < 0.001). At the subject-based, mean sensitivity was significantly higher for interpretation with TS images than that without TS images (73.2% vs. 65.4%; P = 0.003). There was no significant difference in mean specificity (0.93 vs. 0.95; P = 0.083). TS significantly improved overall performance in the detection of various bone metastases.

scholarly journals Nonrigid Registration of Lung CT Images Based on Tissue Features

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Rui Zhang ◽  
Wu Zhou ◽  
Yanjie Li ◽  
Shaode Yu ◽  
Yaoqin Xie
Keyword(s):  
Image Registration ◽  
Medical Image ◽  
Feature Detection ◽  
Ct Images ◽  
Image Process ◽  
Scale Invariant ◽  
Nonrigid Image Registration ◽  
Breathing Motion ◽  
Key Points ◽  
High Gradients

Nonrigid image registration is a prerequisite for various medical image process and analysis applications. Much effort has been devoted to thoracic image registration due to breathing motion. Recently, scale-invariant feature transform (SIFT) has been used in medical image registration and obtained promising results. However, SIFT is apt to detect blob features. Blobs key points are generally detected in smooth areas which may contain few diagnostic points. In general, diagnostic points used in medical image are often vessel crossing points, vascular endpoints, and tissue boundary points, which provide abundant information about vessels and can reflect the motion of lungs accurately. These points generally have high gradients as opposed to blob key points and can be detected by Harris. In this work, we proposed a hybrid feature detection method which can detect tissue features of lungs effectively based on Harris and SIFT. In addition, a novel method which can remove mismatched landmarks is also proposed. A series of thoracic CT images are tested by using the proposed algorithm, and the quantitative and qualitative evaluations show that our method is statistically significantly better than conventional SIFT method especially in the case of large deformation of lungs during respiration.

scholarly journals Evaluation of Deformable Image Registration for Three-Dimensional Temporal Subtraction of Chest Computed Tomography Images

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Ping Yan ◽  
Yoshie Kodera ◽  
Kazuhiro Shimamoto
Keyword(s):  
Computed Tomography ◽  
Image Registration ◽  
Three Dimensional ◽  
Deformable Image Registration ◽  
Ct Images ◽  
Temporal Changes ◽  
Transformation Model ◽  
Chest Computed Tomography ◽  
Temporal Subtraction ◽  
Computed Tomography Images

Purpose. To perform lung image registration for reducing misregistration artifacts on three-dimensional (3D) temporal subtraction of chest computed tomography (CT) images, in order to enhance temporal changes in lung lesions and evaluate these changes after deformable image registration (DIR). Methods. In 10 cases, mutual information (MI) lung mask affine mapping combined with cross-correlation (CC) lung diffeomorphic mapping was used to implement lung volume registration. With advanced normalization tools (ANTs), we used greedy symmetric normalization (greedy SyN) as a transformation model, which involved MI-CC-SyN implementation. The resulting displacement fields were applied to warp the previous (moving) image, which was subsequently subtracted from the current (fixed) image to obtain the lung subtraction image. Results. The average minimum and maximum log-Jacobians were 0.31 and 3.74, respectively. When considering 3D landmark distance, the root-mean-square error changed from an average of 20.82 mm for Pfixed to Pmoving to 0.5 mm for Pwarped to Pfixed. Clear shadows were observed as enhanced lung nodules and lesions in subtraction images. The lesion shadows showed lesion shrinkage changes over time. Lesion tissue morphology was maintained after DIR. Conclusions. DIR (greedy SyN) effectively and accurately enhanced temporal changes in chest CT images and decreased misregistration artifacts in temporal subtraction images.

scholarly journals Temporal subtraction of low-dose and relatively thick-slice CT images with large deformation diffeomorphic metric mapping and adaptive voxel matching for detection of bone metastases

Medicine ◽  
2020 ◽  
Vol 99 (12) ◽  
pp. e19538
Author(s):  
Mitsuteru Tsuchiya ◽  
Takayuki Masui ◽  
Motoyuki Katayama ◽  
Yuki Hayashi ◽  
Takahiro Yamada ◽  
...  
Keyword(s):  
Bone Metastases ◽  
Large Deformation ◽  
Low Dose ◽  
Ct Images ◽  
Temporal Subtraction ◽  
Diffeomorphic Metric Mapping

scholarly journals Temporal Subtraction of Serial CT Images with Large Deformation Diffeomorphic Metric Mapping in the Identification of Bone Metastases

Radiology ◽  
2017 ◽  
Vol 285 (2) ◽  
pp. 629-639 ◽  
Author(s):  
Ryo Sakamoto ◽  
Masahiro Yakami ◽  
Koji Fujimoto ◽  
Keita Nakagomi ◽  
Takeshi Kubo ◽  
...  
Keyword(s):  
Bone Metastases ◽  
Large Deformation ◽  
Ct Images ◽  
Temporal Subtraction ◽  
Serial Ct ◽  
Diffeomorphic Metric Mapping

Predictive Model for Live Birth at 12 Months After Starting In-Vitro Fertilization Treatment

MedPharmRes ◽  
2018 ◽  
Vol 2 (2) ◽  
pp. 5-20
Author(s):  
Vu Ho ◽  
Toan Pham ◽  
Tuong Ho ◽  
Lan Vuong
Keyword(s):  
In Vitro Fertilization ◽  
Live Birth ◽  
Cox Regression ◽  
Financial Burden ◽  
Oocyte Retrieval ◽  
Operating Characteristics ◽  
Vitro Fertilization ◽  
Cox Regression Analysis ◽  
Significant Difference

IVF carries a considerable physical, emotional and financial burden. Therefore, it would be useful to be able to predict the likelihood of success for each couple. The aim of this retrospective cohort study was to develop a prediction model to estimate the probability of a live birth at 12 months after one completed IVF cycle (all fresh and frozen embryo transfers from the same oocyte retrieval). We analyzed data collected from 2600 women undergoing in vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) at a single center in Vietnam between April 2014 and December 2015. All patients received gonadotropin-releasing hormone (GnRH) antagonist stimulation, followed by fresh and/or frozen embryo transfer (FET) on Day 3. Using Cox regression analysis, five predictive factors were identified: female age, total dose of recombinant follicle stimulating hormone used, type of trigger, fresh or FET during the first transfer, and number of subsequent FET after the first transfer. The area under the receiver operating characteristics curve for the final model was 0.63 (95% confidence interval [CI] 0.60‒0.65) and 0.60 (95% CI 0.57‒0.63) for the validation cohort. There was no significant difference between the predicted and observed probabilities of live birth (Hosmer-Lemeshow test, p > 0.05). The model developed had similar discrimination to existing models and could be implemented in clinical practice.

scholarly journals Cloud Detection Based on High Resolution Stereo Pairs of the Geostationary Meteosat Images

2020 ◽  
Vol 12 (3) ◽  
pp. 371 ◽  
Author(s):  
Sahar Dehnavi ◽  
Yasser Maghsoudi ◽  
Klemen Zakšek ◽  
Mohammad Javad Valadan Zoej ◽  
Gunther Seckmeyer ◽  
...  
Keyword(s):  
High Resolution ◽  
Matched Filter ◽  
Stereo Pair ◽  
Cloud Detection ◽  
Operating Characteristics ◽  
Detection Techniques ◽  
Infrared Imager ◽  
Detection Approach ◽  
Considerable Impact ◽  
Image Pairs

Due to the considerable impact of clouds on the energy balance in the atmosphere and on the earth surface, they are of great importance for various applications in meteorology or remote sensing. An important aspect of the cloud research studies is the detection of cloudy pixels from the processing of satellite images. In this research, we investigated a stereographic method on a new set of Meteosat images, namely the combination of the high resolution visible (HRV) channel of the Meteosat-8 Indian Ocean Data Coverage (IODC) as a stereo pair with the HRV channel of the Meteosat Second Generation (MSG) Meteosat-10 image at 0° E. In addition, an approach based on the outputs from stereo analysis was proposed to detect cloudy pixels. This approach is introduced with a 2D-scatterplot based on the parallax value and the minimum intersection distance. The mentioned scatterplot was applied to determine/detect cloudy pixels in various image subsets with different amounts of cloud cover. Apart from the general advantage of the applied stereography method, which only depends on geometric relationships, the cloud detection results are also improved because: (1) The stereo pair is the HRV bands of the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) sensor, with the highest spatial resolution available from the Meteosat geostationary platform; and (2) the time difference between the image pairs is nearly 5 s, which improves the matching results and also decreases the effect of cloud movements. In order to prove this improvement, the results of this stereo-based approach were compared with three different reflectance-based target detection techniques, including the adaptive coherent estimator (ACE), constrained energy minimization (CEM), and matched filter (MF). The comparison of the receiver operating characteristics (ROC) detection curves and the area under these curves (AUC) showed better detection results with the proposed method. The AUC value was 0.79, 0.90, 0.90, and 0.93 respectively for ACE, CEM, MF, and the proposed stereo-based detection approach. The results of this research shall enable a more realistic modelling of down-welling solar irradiance in the future.

scholarly journals Optimizing Manufacturing and Osseointegration of Ti6Al4V Implants through Precision Casting and Calcium and Phosphorus Ion Implantation? In Vivo Results of a Large-Scale Animal Trial

Materials ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1670 ◽  
Author(s):  
Wölfle-Roos JV ◽  
Katmer Amet B ◽  
Fiedler J ◽  
Michels H ◽  
Kappelt G ◽  
...  
Keyword(s):  
Ion Implantation ◽  
Large Scale ◽  
In Vivo Studies ◽  
Control Group ◽  
Implant Surface ◽  
Precision Casting ◽  
Pull Out ◽  
Significant Difference ◽  
Calcium And Phosphorus

Background: Uncemented implants are still associated with several major challenges, especially with regard to their manufacturing and their osseointegration. In this study, a novel manufacturing technique—an optimized form of precision casting—and a novel surface modification to promote osseointegration—calcium and phosphorus ion implantation into the implant surface—were tested in vivo. Methods: Cylindrical Ti6Al4V implants were inserted bilaterally into the tibia of 110 rats. We compared two generations of cast Ti6Al4V implants (CAST 1st GEN, n = 22, and CAST 2nd GEN, n = 22) as well as cast 2nd GEN Ti6Al4V implants with calcium (CAST + CA, n = 22) and phosphorus (CAST + P, n = 22) ion implantation to standard machined Ti6Al4V implants (control, n = 22). After 4 and 12 weeks, maximal pull-out force and bone-to-implant contact rate (BIC) were measured and compared between all five groups. Results: There was no significant difference between all five groups after 4 weeks or 12 weeks with regard to pull-out force (p > 0.05, Kruskal Wallis test). Histomorphometric analysis showed no significant difference of BIC after 4 weeks (p > 0.05, Kruskal–Wallis test), whereas there was a trend towards a higher BIC in the CAST + P group (54.8% ± 15.2%), especially compared to the control group (38.6% ± 12.8%) after 12 weeks (p = 0.053, Kruskal–Wallis test). Conclusion: In this study, we found no indication of inferiority of Ti6Al4V implants cast with the optimized centrifugal precision casting technique of the second generation compared to standard Ti6Al4V implants. As the employed manufacturing process holds considerable economic potential, mainly due to a significantly decreased material demand per implant by casting near net-shape instead of milling away most of the starting ingot, its application in manufacturing uncemented implants seems promising. However, no significant advantages of calcium or phosphorus ion implantation could be observed in this study. Due to the promising results of ion implantation in previous in vitro and in vivo studies, further in vivo studies with different ion implantation conditions should be considered.

scholarly journals Joint regression and learning from pairwise rankings for personalized image aesthetic assessment

2021 ◽  
Author(s):  
Jin Zhou ◽  
Qing Zhang ◽  
Jian-Hao Fan ◽  
Wei Sun ◽  
Wei-Shi Zheng
Keyword(s):  
Large Scale ◽  
Assessment Model ◽  
Generic Model ◽  
Small Subset ◽  
Deep Convolutional Neural Networks ◽  
Personal Taste ◽  
Hinge Loss ◽  
Novel Approach ◽  
Large Scale Dataset ◽  
Image Pairs

AbstractRecent image aesthetic assessment methods have achieved remarkable progress due to the emergence of deep convolutional neural networks (CNNs). However, these methods focus primarily on predicting generally perceived preference of an image, making them usually have limited practicability, since each user may have completely different preferences for the same image. To address this problem, this paper presents a novel approach for predicting personalized image aesthetics that fit an individual user’s personal taste. We achieve this in a coarse to fine manner, by joint regression and learning from pairwise rankings. Specifically, we first collect a small subset of personal images from a user and invite him/her to rank the preference of some randomly sampled image pairs. We then search for the K-nearest neighbors of the personal images within a large-scale dataset labeled with average human aesthetic scores, and use these images as well as the associated scores to train a generic aesthetic assessment model by CNN-based regression. Next, we fine-tune the generic model to accommodate the personal preference by training over the rankings with a pairwise hinge loss. Experiments demonstrate that our method can effectively learn personalized image aesthetic preferences, clearly outperforming state-of-the-art methods. Moreover, we show that the learned personalized image aesthetic benefits a wide variety of applications.

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