Leukemia is a hematologic cancer which develops in blood tissue and triggers rapid production of immature and abnormal shaped white blood cells. Based on statistics it is found that the leukemia is one of the leading causes of death in men and women alike. Microscopic examination of blood sample or bone marrow smear is the most effective technique for diagnosis of leukemia. Pathologists analyze microscopic samples to make diagnostic assessments on the basis of characteristic cell features. Recently, computerized methods for cancer detection have been explored towards minimizing human intervention and providing accurate clinical information. This paper presents an algorithm for automated image based acute leukemia detection systems. The method implemented uses basic enhancement, morphology, filtering and segmenting technique to extract region of interest using k -means clustering algorithm. The proposed algorithm achieved an accuracy of 92.8% and is tested with Nearest Neighbor (kNN) and Naïve Bayes Classifier on the dataset of 60 samples.
Computer Aided Diagnosis has emerged as an indispensible technique for validating the opinion of radiologists in CT interpretation. This paper presents a deep 3D Convolutional Neural Network (CNN) architecture for automated CT scan-based lung cancer detection system. It utilizes three dimensional spatial information to learn highly discriminative 3 dimensional features instead of 2D features like texture or geometric shape whick need to be generated manually. The proposed deep learning method automatically extracts the 3D features on the basis of spatiotemporal statistics.The developed model is end-to-end and is able to predict malignancy of each voxel for given input scan. Simulation results demonstrate the effectiveness of proposed 3D CNN network for classification of lung nodule in-spite of limited computational capabilities.
Abstract-A greenhouse (also known as glass house) is a building where plants are kept in a controlled environment. Greenhouses are made by transparent materials such as glass and plastics and thus sometimes it is necessary to change the environmental condition in the greenhouse. This research paperdeals with aneconomical and efficient system to monitor and modify the weather of the greenhouse. An embedded system is used to monitor and change different parameters which directly affect plants. Sensors are used to monitor the temperature, soil moisture, humidity and sun light. According to the interpretation of the sensors, microcontroller controls various devices so that a constant weather condition can be maintained.The complete project is aimed to implement on Arduino Uno, an open source software which is simple to use and maintenance cost is low. It is used to control all devices and sensors.
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