FC2 Signal and Image Processing II
Time : 15:20~16:50
Room : Crystal
Chair : Prof.Hyoungseop Kim (Kyushu Institute of Tecnology, Japan)
15:20~15:35        FC2-1
Registration of Phalange Region from CR Images Based on Genetic Algorithm

Kouhei Kawagoe, Hyoungseop Kim(Kyushu Institute of Technology, Japan)

In Japan, the number of patients with osteoporosis and rheumatoid arthritis is increasing. Image diagnosis using CR images is effective for osteoporosis and rheumatoid arthritis. Development of a CAD system is important for reducing burdens on doctors. In this paper, we propose an automatic registration algorithm in the CAD system. In the proposed method, the genetic algorithm is used to register bone regions between identical parts of the same subject with different time series. In the experiment, the proposed method is applied to 176 bone area, and 98.14 % of TPR, 1.85 % of FPR are obtained
15:35~15:50        FC2-2
Automatic Extraction of Abnormalities on Temporal CT Subtraction Images Using Sparse Coding and 3D-CNN

Yuichiro Koizumi, Hyoungseop Kim(Kyushu Institute of Technology, Japan)

In recent years, the proportion of deaths from cancer tends to increase in Japan, especially the number of deaths from lung cancer is increasing. In this paper, we develop a CAD system for automatic detection of lesion candidate regions such as lung nodules or ground glass opacity (GGO) from 3D CT images. We applied our method to 51 cases and True Positive rate (TP) of 79.81 % and False Positive rate (FP) of 37.65 % are obtained.
15:50~16:05        FC2-3
Detection of Grasping Position from Video Images Based on SSD

Kitayama Taichi, Hyoungseop Kim(Kyushu Institute of Technology, Japan)

Recently, consistent container transportation of roads and ships is mainstream of international freight transport. Because of various factors, automation of cargo handling work is required at the container terminal. Various causes are decrement of future labor force population by an increasing trend of container moving amount and declining birthrate and aging population. Therefore, this study presents the relative position of hanger and container measurement technology using Single Shot Multibox Detector (SSD) for the purpose of improvement of cargo handling work efficiency and unmanned cont
16:05~16:20        FC2-4
Wide Residual Networks for Semantic Segmentation

Yoshiki Nakayama, Hyoungseop Kim(Kyushu Institute of Technology, Japan)

In the task of object recognition, convolutional neural networks (CNNs) have achieved high performance. In addition, these CNNs are also applied to the field of semantic image segmentation. However, applying the classification models to semantic segmentation tasks has a problem, lack of global context and reduction in resolution. In this work, we propose global context module and high resolution path in order to solve above problems. By simply combining them with an existing classification model, our methods yield high-accuracy segmentation models.

<<   1   >>