Attribute-guided image generation of three-dimensional computed tomography images of lung nodules using a generative adversarial network

2020 ◽  
Vol 126 ◽  
pp. 104032
Author(s):  
Mizuho Nishio ◽  
Chisako Muramatsu ◽  
Shunjiro Noguchi ◽  
Hirotsugu Nakai ◽  
Koji Fujimoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
Lung Nodules ◽  
Image Generation ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Computed Tomography Images

scholarly journals Development of Computer-aided Diagnostic System for Detection of Lung Nodules in Three-dimensional Computed Tomography Images

2006 ◽  
Vol 62 (4) ◽  
pp. 555-564 ◽  
Author(s):  
Megumi Yamamoto ◽  
Takayuki Ishida ◽  
Ikuo Kawashita ◽  
Masayuki Kagemoto ◽  
Koichi Fujikawa ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Three Dimensional ◽  
Diagnostic System ◽  
Lung Nodules ◽  
Computed Tomography Images ◽  
Computer Aided

scholarly journals Immersive 3D virtual reality imaging in planning minimally invasive and complex adult cardiac surgery

2020 ◽  
Vol 1 (1) ◽  
pp. 62-70
Author(s):  
Amir H Sadeghi ◽  
Wouter Bakhuis ◽  
Frank Van Schaagen ◽  
Frans B S Oei ◽  
Jos A Bekkers ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Virtual Reality ◽  
Cardiac Surgery ◽  
Heart Surgery ◽  
Preoperative Planning ◽  
Operating Time ◽  
Three Dimensional ◽  
Cardiothoracic Surgery ◽  
Planning Tool ◽  
Computed Tomography Images

Abstract Aims Increased complexity in cardiac surgery over the last decades necessitates more precise preoperative planning to minimize operating time, to limit the risk of complications during surgery and to aim for the best possible patient outcome. Novel, more realistic, and more immersive techniques, such as three-dimensional (3D) virtual reality (VR) could potentially contribute to the preoperative planning phase. This study shows our initial experience on the implementation of immersive VR technology as a complementary research-based imaging tool for preoperative planning in cardiothoracic surgery. In addition, essentials to set up and implement a VR platform are described. Methods Six patients who underwent cardiac surgery at the Erasmus Medical Center, Rotterdam, The Netherlands, between March 2020 and August 2020, were included, based on request by the surgeon and availability of computed tomography images. After 3D VR rendering and 3D segmentation of specific structures, the reconstruction was analysed via a head mount display. All participating surgeons (n = 5) filled out a questionnaire to evaluate the use of VR as preoperative planning tool for surgery. Conclusion Our study demonstrates that immersive 3D VR visualization of anatomy might be beneficial as a supplementary preoperative planning tool for cardiothoracic surgery, and further research on this topic may be considered to implement this innovative tool in daily clinical practice. Lay summary Over the past decades, surgery on the heart and vessels is becoming more and more complex, necessitating more precise and accurate preoperative planning. Nowadays, operative planning is feasible on flat, two-dimensional computer screens, however, requiring a lot of spatial and three-dimensional (3D) thinking of the surgeon. Since immersive 3D virtual reality (VR) is an upcoming imaging technique with promising results in other fields of surgery, we aimed in this study to explore the additional value of this technique in heart surgery. Our surgeons planned six different heart operations by visualizing computed tomography scans with a dedicated VR headset, enabling them to visualize the patient’s anatomy in an immersive and 3D environment. The outcomes of this preliminary study are positive, with a much more reality-like simulation for the surgeon. In such, VR could potentially be beneficial as a preoperative planning tool for complex heart surgery.

Total Wrist Arthroplasty Alignment and Its Potential Association with Clinical Outcomes

2021 ◽  
Author(s):  
Bardiya Akhbari ◽  
Kalpit N. Shah ◽  
Amy M. Morton ◽  
Janine Molino ◽  
Douglas C. Moore ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Clinical Outcomes ◽  
Three Dimensional ◽  
Radial Component ◽  
Single Type ◽  
Radiographic Images ◽  
Computed Tomography Images ◽  
Total Wrist Arthroplasty ◽  
Flexion Extension ◽  
Wrist Arthroplasty

Abstract Purpose There is a lack of quantitative research that describes the alignment and, more importantly, the effects of malalignment on total wrist arthroplasty (TWA). The main goal of this pilot study was to assess the alignment of TWA components in radiographic images and compare them with measures computed by three-dimensional analysis. Using these measures, we then determined if malalignment is associated with range of motion (ROM) or clinical outcomes (PRWHE, PROMIS, QuickDash, and grip strength). Methods Six osteoarthritic patients with a single type of TWA were recruited. Radiographic images, computed tomography images, and clinical outcomes of the wrists were recorded. Using posteroanterior and lateral radiographs, alignment measurements were defined for the radial and carpal components. Radiographic measurements were validated with models reconstructed from computed tomography images using Bland–Altman analysis. Biplanar videoradiography (<1mm and <1 degree accuracy) was used to capture and compute ROM of the TWA components. Linear regression assessed the associations between alignment and outcomes. Results Radiographic measures had a 95% limit-of-agreement (mean difference ±  1.96 × SD) of 3 degrees and 3mm with three-dimensional values, except for the measures of the carpal component in the lateral view. In our small cohort, wrist flexion–extension and radial–ulnar deviation were correlated with volar–dorsal tilt and volar–dorsal offset of the radial component and demonstrated a ROM increase of 3.7 and 1.6 degrees per degree increase in volar tilt, and 10.8 and 4.2 degrees per every millimeter increase in volar offset. The carpal component's higher volar tilt was also associated with improvements in patient-reported pain. Conclusions We determined metrics describing the alignment of TWA, and found the volar tilt and volar offset of the radial component could potentially influence the replaced wrist's ROM. Clinical Relevance TWA component alignment can be measured reliably in radiographs, and may be associated with clinical outcomes. Future studies must evaluate its role in a larger cohort.

scholarly journals Three-dimensional assessment of the anterior and inferior loop of the inferior alveolar nerve using computed tomography images in patients with and without mandibular asymmetry

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jae-Young Kim ◽  
Michael D. Han ◽  
Kug Jin Jeon ◽  
Jong-Ki Huh ◽  
Kwang-Ho Park
Keyword(s):  
Computed Tomography ◽  
Symmetry Group ◽  
Three Dimensional ◽  
Inferior Alveolar Nerve ◽  
Mental Foramen ◽  
3D Analysis ◽  
Mandibular Asymmetry ◽  
Computed Tomography Images ◽  
Significant Difference ◽  
Mandibular Body

Abstract Background The purpose of this study was to investigate the differences in configuration and dimensions of the anterior loop of the inferior alveolar nerve (ALIAN) in patients with and without mandibular asymmetry. Method Preoperative computed tomography images of patients who had undergone orthognathic surgery from January 2016 to December 2018 at a single institution were analyzed. Subjects were classified into two groups as “Asymmetry group” and “Symmetry group”. The distance from the most anterior and most inferior points of the ALIAN (IANant and IANinf) to the vertical and horizontal reference planes were measured (dAnt and dInf). The distance from IANant and IANinf to the mental foramen were also calculated (dAnt_MF and dInf_MF). The length of the mandibular body and symphysis area were measured. All measurements were analyzed using 3D analysis software. Results There were 57 total eligible subjects. In the Asymmetry group, dAnt and dAnt_MF on the non-deviated side were significantly longer than the deviated side (p < 0.001). dInf_MF on the non-deviated side was also significantly longer than the deviated side (p = 0.001). Mandibular body length was significantly longer on the non-deviated side (p < 0.001). There was no significant difference in length in the symphysis area (p = 0.623). In the Symmetry group, there was no difference between the left and right sides for all variables. Conclusion In asymmetric patients, there is a difference tendency in the ALIAN between the deviated and non-deviated sides. In patients with mandibular asymmetry, this should be considered during surgery in the anterior mandible.

scholarly journals CDL-GAN: Contrastive Distance Learning Generative Adversarial Network for Image Generation

2021 ◽  
Vol 11 (4) ◽  
pp. 1380
Author(s):  
Yingbo Zhou ◽  
Pengcheng Zhao ◽  
Weiqin Tong ◽  
Yongxin Zhu
Keyword(s):  
Distance Learning ◽  
Feature Learning ◽  
Image Synthesis ◽  
Image Feature ◽  
Generative Adversarial Networks ◽  
Image Generation ◽  
Generative Adversarial Network ◽  
Feature Representations ◽  
Adversarial Network ◽  
Public Datasets

While Generative Adversarial Networks (GANs) have shown promising performance in image generation, they suffer from numerous issues such as mode collapse and training instability. To stabilize GAN training and improve image synthesis quality with diversity, we propose a simple yet effective approach as Contrastive Distance Learning GAN (CDL-GAN) in this paper. Specifically, we add Consistent Contrastive Distance (CoCD) and Characteristic Contrastive Distance (ChCD) into a principled framework to improve GAN performance. The CoCD explicitly maximizes the ratio of the distance between generated images and the increment between noise vectors to strengthen image feature learning for the generator. The ChCD measures the sampling distance of the encoded images in Euler space to boost feature representations for the discriminator. We model the framework by employing Siamese Network as a module into GANs without any modification on the backbone. Both qualitative and quantitative experiments conducted on three public datasets demonstrate the effectiveness of our method.

Does Generative Adversarial Network (GAN) help in SRAF image generation?

2021 ◽  
Author(s):  
Jialu Huang ◽  
Ying Huang ◽  
Yan-ting Lin ◽  
Zi-yang Liu ◽  
Yang Lin ◽  
...  
Keyword(s):  
Image Generation ◽  
Generative Adversarial Network ◽  
Adversarial Network
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