Deep Convolutional Neural Network Based Single Tree Detection Using Volumetric Module From Airborne Lidar Data

There was an undeniable success of Deep Learning networks for visual data analytics such as object detection and segmentation in recent years, while the adaptation to tree detection has been rare. In this paper, we pursue to achieve individual tree identification, defined as a detection of an individual tree as each object, with deep convolutional neural networks to create and update tree inventories using LiDAR information. The first objective was to provide a suitable dataset that can be used to test such networks and to create a module that attempts to increase the 3D object detection algorithms' detection accuracy. This novel dataset was created by fusing LiDAR data gathered by Teledyne Optech with field data collected by York University. The second was to develop an appropriate accuracy increasing volumetric module. For this module, the learnable weights concept was introduced, which enable to increase detection precision of the object detection algorithm

Prediction of Cancer Patient Outcomes Based on Artificial Intelligence

Knowledge-based outcome predictions are common before radiotherapy. Because there are various treatment techniques, numerous factors must be considered in predicting cancer patient outcomes. As expectations surrounding personalized radiotherapy using complex data have increased, studies on outcome predictions using artificial intelligence have also increased. Representative artificial intelligence techniques used to predict the outcomes of cancer patients in the field of radiation oncology include collecting and processing big data, text mining of clinical literature, and machine learning for implementing prediction models. Here, methods of data preparation and model construction to predict rates of survival and toxicity using artificial intelligence are described

Does Tumor Size Influence the Diagnostic Accuracy of Ultrasound-Guided Fine-Needle Aspiration Cytology for Thyroid Nodules?

Background. Fine-needle aspiration cytology (FNAC) is diagnostic standard for thyroid nodules. However, the influence of size on FNAC accuracy remains unclear especially in too small or too large thyroid nodules. The objective of this retrospective cohort study was to investigate the effect of nodule size on FNAC accuracy. Methods. All consecutive patients who underwent thyroidectomy for nodules in 2010 were enrolled. FNAC results (according to the Bethesda system) were compared to pathological diagnosis. The nodules were categorized into groups A–E on the basis of maximal diameter on ultrasound (≤0.5, >0.5–1, >1-2, >2–4, and >4 cm, resp.). Results. There were 502 cases with 690 nodules. Overall FNAC sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 95.4%, 98.2%, 99.4%, 86.4%, and 96.0%, respectively. False-negative rates (FNRs) of groups A–E were 3.2%, 5.1%, 1.3%, 13.3%, and 50%, respectively. Accuracy rates of groups A–E were 96.8%, 94.8%, 99%, 94.7%, and 87.5%, respectively. Conclusion. Although accuracy rates of FNAC in thyroid nodules smaller than 0.5 cm are comparable to the other group, thyroid nodules larger than 4 cm with benign cytology carry a higher risk of malignancy, which suggest that those should be considered for intensive follow-up or repeated biopsy

Acute high-dose and chronic lifetime exposure to alcohol consumption and differentiated thyroid cancer: T-CALOS Korea

Source: doi: 10.1371/journal.pone.0151562Background: This study evaluated the effects of acute high-dose and chronic lifetime exposure to alcohol and exposure patterns on the development of differentiated thyroid cancer (DTC). Methods: The Thyroid Cancer Longitudinal Study (T-CALOS) included 2,258 DTC patients (449 men and 1,809 women) and 22,580 healthy participants (4,490 men and 18,090 women) who were individually matched by age, gender, and enrollment year. In-person interviews were conducted with a structured questionnaire to obtain epidemiologic data. Clinicopathologic features of the patients were obtained by chart reviews. Odds ratios (ORs) and 95% confidence intervals (95%CI) were estimated using conditional regression models. Results: While light or moderate drinking behavior was related to a reduced risk of DTC, acute heavy alcohol consumption (151 g or more per event or on a single occasion) was associated with increased risks in men (OR = 2.22, 95%CI = 1.27–3.87) and women (OR = 3.61, 95%CI = 1.52–8.58) compared with never-drinkers. The consumption of alcohol for 31 or more years was a significant risk factor for DTC for both men (31–40 years: OR = 1.58, 95%CI = 1.10– 2.28; 41+ years: OR = 3.46, 95%CI = 2.06–5.80) and women (31–40 years: OR = 2.18, 95%CI = 1.62–2.92; 41+ years: OR = 2.71, 95%CI = 1.36–5.05) compared with never-drinkers. The consumption of a large amount of alcohol on a single occasion was also a significant risk factor, even after restricting DTC outcomes to tumor size, lymph node metastasis, extrathyroidal extension and TNM stage. Conclusion: The findings of this study suggest that the threshold effects of acute high-dose alcohol consumption and long-term alcohol consumption are linked to an increased risk of DTC

Systematic Review of Surgical Approaches for Adrenal Tumors: Lateral Transperitoneal versus Posterior Retroperitoneal and Laparoscopic versus Robotic Adrenalectomy

Background. Laparoscopic lateral transperitoneal adrenalectomy (LTA) has been the standard method for resecting benign adrenal gland tumors. Recently, however, laparoscopic posterior retroperitoneal adrenalectomy (PRA) has been more popular as an alternative method. This systematic review evaluates current evidence on adrenalectomy techniques, comparing laparoscopic LTA with PRA and laparoscopic adrenalectomy with robotic adrenalectomy. Methods. PubMed, Embase, and ISI Web of Knowledge databases were searched systematically for studies comparing surgical outcomes of laparoscopic LTA versus PRA and laparoscopic versus robotic adrenalectomy. The studies were evaluated according to the PRISMA statement. Results. Eight studies comparing laparoscopic PRA and LTA showed that laparoscopic PRA was superior or at least comparable to laparoscopic LTA in operation time, blood loss, pain score, hospital stay, and return to normal activity. Conversion rates and complication rates were similar. Six studies comparing robotic and laparoscopic adrenalectomy found that outcomes and complications were similar. Conclusion. Laparoscopic PRA was more effective than LTA, especially in reducing operation time and hospital stay, but there was no evidence showing that robotic adrenalectomy was superior to laparoscopic adrenalectomy. Cost reductions and further technical advances are needed for wider application of robotic adrenalectomy

Precise orientation control of a liquid crystal organic semiconductor via anisotropic surface treatment

We report a three-dimensional (3D) molecular orientation control of a liquid crystal organic semiconductor (LC-OSC) based on the long-range ordering characteristic of an LC material. To this end, a synthetic LC-OSC molecule, MeOPh-BTBT-C8, with a fluidic nematic (N) phase that is essential for alignment control over a large area and a smectic E (SmE) phase showing high ordering, was prepared. A simple flipping of a sandwich cell made of the LC-OSC material between the top and bottom substrates that have uniaxial-planar degenerated alignment as well as crossed rubbing directions responds to the given surface anchoring condition and temperature gradient. Optical observation of the alignment-controlled LC-OSC was carried out by polarized optical microscopy (POM), and the corresponding charge carrier mobility was also measured by fabricating organic field-effect transistors (OFETs). Our platform offers a facile approach for multidirectional and multifunctional organic electronic devices using the stimulus-response characteristics of LC materials

Quantitative Understanding of Ionic Channel Network Variation in Nafion with Hydration Using Current Sensing Atomic Force Microscopy

Proton exchange membranes are an essential component of proton-exchange membrane fuel cells (PEMFC). Their performance is directly related to the development of ionic channel networks through hydration. Current sensing atomic force microscopy (CSAFM) can map the local conductance and morphology of a sample surface with sub-nano resolution simultaneously by applying a bias voltage between the conducting tip and sample holder. In this study, the ionic channel network variation of Nafion by hydration has been quantitatively characterized based on the basic principles of electrodynamics and CSAFM. A nano-sized PEMFC has been created using a Pt-coated tip of CSAFM and one side Pt-coated Nafion, and studied under different relative humidity (RH) conditions. The results have been systematically analyzed. First, the morphology of PEMFC under each RH has been studied using line profile and surface roughness. Second, the CSAFM image has been analyzed statistically through the peak value and full-width half-maximum of the histograms. Third, the number of protons moving through the ionic channel network (NPMI) has been derived and used to understand ionic channel network variation by hydration. This study develops a quantitative method to comprehend variations in the ionic channel network by calculating the movement of protons into the ionic channel network based on CSAFM images. To verify the method, a comparison is made between the NPMI and the changes in proton conductivity under different RH conditions and it reveals a good agreement. This developed method can offer a quantitative approach for characterizing the morphological structure of PEM. Also, it can provide a quantitative tool for interpretating CSAFM images