http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
AHM Zadidul Karim,Md Abdullah Al Mahmud,Md Sazal Miah,Shikder Shafiul Bashar,Seungmin Oh,Jinsul Kim,Maliha Marium 한국디지털콘텐츠학회 2020 The Journal of Contents Computing Vol.2 No.2
Photoplethesmography (PPG) is a low cost, non-invasive heart Rate (HR) monitoring process. It contains important health information. So, based on these characteristics this paper has taken step to go with it. PPG signal recorded very easily from the surface of the skin by using wearable device. So, during exercise PPG signal is corrupted heavily by Motion Artifact (MA). The interest of this paper is to work on removing the MA and reconstruction of clean PPG signal. This paper has worked on two stages. One is the tracking of PPG signal and detection of the peak of ECG signal.
Biomedical Image Processing: Spine Tumor Detection from MRI image using MATLAB
Md. Abdullah Al Mahmud,AHM Zadidul Karim,Md. Sazal Miah,Yeonggwang Kim,Jinsul Kim,Shikder Shafiul Bashar 한국디지털콘텐츠학회 2020 The Journal of Contents Computing Vol.2 No.2
The main goal of this research is to the detection of spine tumors with the results provided by image processing of the patient’s MRI image. Especially, we focus on the methodology of image processing. We have also discussed the technique of detecting the fractional area of the spine tumor. A spine tumor is difficult to detect. For detecting tumors accurately Magnetic resonance imaging (MRI) is a common approach. It is a non-invasive technique for generating 3-dimensional topographic pictures of the human body. MRI is frequently utilized for the identification of various irregularities in soft tissues, for example, the Spine, lesions, and tumors. Nowadays clinical Image processing is the most difficult and arising field. It has already been mentioned that the main focus of this research is to develop a strategy to identify and extraction of Spine tumors from a patient"s MRI im-ages of the Spine. This technique incorporates segmentation and morphological operations and various noise reduction function which are the fundamental ideas of image processing. Our proposed method will take input from MRI images. Input image will convert to a grayscale image, then it will be adjusted based on the maximum intensity level, for avoiding extra data. For identifying the range of the spine cross-section images will be converted to binary data. It will also calculate the area of the spine cross-section. Then adjusted image will be converting to a binary im-age in order to eliminate the boundary and detect tumor affected area. Finally, we calculate the volume of the tumor with the help of MATLAB software.