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RISS 인기검색어
- 검색키워드
- 저자 : Md Abdullah Al Mahmud (검색결과 3 건)
- 무료
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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.
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Mohammad Mahfuzur Rahman,Md. Abdullah Al Mahmud,Farid Uddin Ahmed 한국산림과학회 2017 Forest Science And Technology Vol.13 No.3
Lack ofnon-forestry incomesources for the forest-dependent community was oneof the major causes of continued biodiversity loss in Chunati Wildlife Sanctuary (CWS). A livelihood support program was implemented from July 2012 through June 2015 to reduce people’s forest-dependence for their livelihoods. We evaluated the efficacy of this program in enhancing the biodiversity health of CWS. An Ordinary Least Square regression framework was used to estimate the difference in difference of the income between the control and the treatment households. Alongside, the biodiversity attributes of the CWS were measured in 2012 and 2015 and were compared. The intervention increased a treatment household’s monthly non-forestry income by BDT11,781 and decreased its monthly forest income by BDT2128. In contrast, with increased natural regeneration of 8.43%, 12 out of the 16 major species at CWS showed increased importance value index (IVI). The IVI increased by 48.03% for Acacia auriculiformis and decreased by 56.30% and 31.76% for Dipterocarpus turbinatus and Tectona grandis, respectively. As confirmed by the households, this biodiversity improvement could be attributed to the livelihood intervention program at CWS. Continued monitoring is important to sustain the successes of the program.
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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.
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