Localization Uncertainty Estimation for Anchor-Free Object Detection

Since many safety-critical systems, such as surgical robots and autonomous driving cars, are in unstable environments with sensor noise and incomplete data, it is desirable for object detectors to take into account the confidence of localization prediction. There are three limitations of the prior uncertainty estimation methods for anchor-based object detection. 1) They model the uncertainty based on object properties having different characteristics, such as location (center point) and scale (width, height). 2) they model a box offset and ground-truth as Gaussian distribution and Dirac delta distribution, which leads to the model misspecification problem. Because the Dirac delta distribution is not exactly represented as Gaussian, i.e., for any $\mu$ and $\Sigma$. 3) Since anchor-based methods are sensitive to hyper-parameters of anchor, the localization uncertainty modeling is also sensitive to these parameters. Therefore, we propose a new localization uncertainty estimation method called Gaussian-FCOS for anchor-free object detection. Our method captures the uncertainty based on four directions of box offsets~(left, right, top, bottom) that have similar properties, which enables to capture which direction is uncertain and provide a quantitative value in range~[0, 1]. To this end, we design a new uncertainty loss, negative power log-likelihood loss, to measure uncertainty by weighting IoU to the likelihood loss, which alleviates the model misspecification problem. Experiments on COCO datasets demonstrate that our Gaussian-FCOS reduces false positives and finds more missing-objects by mitigating over-confidence scores with the estimated uncertainty. We hope Gaussian-FCOS serves as a crucial component for the reliability-required task

Automatic 3D Model Generation based on a Matching of Adaptive Control Points

Abstract The use of a 3D model helps to diagnosis and accurately locate a disease where it is neither available, nor can be exactly measured in a 2D image. Therefore, highly accurate software for a 3D model of vessel is required for an accurate diagnosis of patients. We have generated standard vessel because the shape of the arterial is different for each individual vessel, where the standard vessel can be adjusted to suit individual vessel. In this paper, we propose a new approach for an automatic 3D model generation based on a matching of adaptive control points. The proposed method is carried out in three steps. First, standard and individual vessels are acquired. The standard vessel is acquired by a 3D model projection, while the individual vessel of the first segmented vessel bifurcation is obtained. Second is matching the corresponding control points between the standard and individual vessels, where a set of control and corner points are automatically extracted using the Harris corner detector. If control points exist between corner points in an individual vessel, it is adaptively interpolated in the corresponding standard vessel which is proportional to the distance ratio. And then, the control points of corresponding individual vessel match with those control points of standard vessel. Finally, we apply warping on the standard vessel to suit the individual vessel using the TPS (Thin Plate Spline) interpolation function. For experiments, we used angiograms of various patients from a coronary angiography in Sanggye Paik Hospital

Long-term evaluation of the prognosis of super hydrophilic surface treated CA implants: a retrospective clinical study

This study was performed to evaluate the long-term clinical efficacy of the CA implants (Osstem Implant, Busan, Korea), calcium-modified surfaced treated implants on acid-etched surfaces sandblasted with alumina. From January 2013 to December 2015, 258 implants of 120 patients placed between 2013 and 2015 were retrospectively studied. Using medical records and periapical radiographs, sex, age, location, fixture width and length of placed implants, presence or absence of bone graft, types of bone substitutes and membrane used for bone grafting, primary and secondary stability, initial and delayed complications, and marginal bone loss were investigated. The success rate and survival rate of the implants in each group were analyzed retrospectively based on the criteria suggested by Albrektsson et al. Between 2013 and 2015, with a follow-up longer than 5years, 258 implants with an average diameter of 4.63mm (3.5–5.5mm) and an average length of 9.94mm (7.0–13.0mm) were placed in a total of 120 patients (61 males and 59 females) with a mean age of 63.7years for an average of 62months of observation period. The survival rate was 97.3%, the success rate was 94.2%, and the average final marginal bone loss was 0.074mm. The CA implants manufactured with the improved surface treatment method exhibited a survival rate of 97.3% and a success rate of 94.2% over an average observation period of 62months. The implants were not affected by most factors and had very high survival and success rates over a long period of observation. In particular, the stability of the implant was excellent, with no cases of failed implants in delayed placement after bone grafting and a healing period

Visfatin Induces Sickness Responses in the Brain

BACKGROUND/OBJECTIVE: Visfatin, also known as nicotiamide phosphoribosyltransferase or pre-B cell colony enhancing factor, is a pro-inflammatory cytokine whose serum level is increased in sepsis and cancer as well as in obesity. Here we report a pro-inflammatory role of visfatin in the brain, to mediate sickness responses including anorexia, hyperthermia and hypoactivity. METHODOLOGY: Rats were intracerebroventricularly (ICV) injected with visfatin, and changes in food intake, body weight, body temperature and locomotor activity were monitored. Real-time PCR was applied to determine the expressions of pro-inflammatory cytokines, proopiomelanocortin (POMC) and prostaglandin-synthesizing enzymes in their brain. To determine the roles of cyclooxygenase (COX) and melanocortin in the visfatin action, rats were ICV-injected with visfatin with or without SHU9119, a melanocortin receptor antagonist, or indomethacin, a COX inhibitor, and their sickness behaviors were evaluated. PRINCIPAL FINDINGS: Administration of visfatin decreased food intake, body weight and locomotor activity and increased body temperature. Visfatin evoked significant increases in the levels of pro-inflammatory cytokines, prostaglandin-synthesizing enzymes and POMC, an anorexigenic neuropeptide. Indomethacin attenuated the effects of visfatin on hyperthermia and hypoactivity, but not anorexia. Further, SHU9119 blocked visfatin-induced anorexia but did not affect hyperthermia or hypoactivity. CONCLUSIONS: Visfatin induced sickness responses via regulation of COX and the melanocortin pathway in the brain