Problem statement: Computer Tomography (CT) has been considered as the most sensitive imaging technique for early detection of lung cancer. Approach: On the other hand, there is a requirement for automated methodology to make use of large amount of data obtained CT images. Computer Aided Diagnosis (CAD) can be used efficiently for early detection of Lung Cancer. Results: The usage of existing CAD system for early detection of lung cancer with the help of CT images has been unsatisfactory because of its low sensitivity and False Positive Rates (FPR). This study presents a CAD system which can automatically detect the lung cancer nodules with reduction in false positive rates. In this study, different image processing techniques are applied initially in order to obtain the lung region from the CT scan chest images. Then the segmentation is carried with the help of Fuzzy Possibility C Mean (FPCM) clustering algorithm. Conclusion/Recommendations: Finally for automatic detection of cancer nodules, Support Vector Machine (SVM) is used which helps in better classification of cancer nodules. The experimentation is conducted for the proposed technique by 1000 CT images collected from the reputed hospital.

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Problem statement: Most of the previous study in diagnosis of kidney stone identifies a mere presence or absence of the stones in the kidney. However proposal in our study even present an early detection of kidney stones which helps to change the diet conditions and prevent the formation of stones. Approach: The study presented a scheme for ultrasound kidney image diagnosis for stone and its early detection based on improved seeded region growing based segmentation and classification of kidney images with stone sizes. With segmented portions of the images the intensity threshold variation helps in identifying multiple classes to classify the images as normal, stone and early stone stages. The improved semiautomatic Seeded Region Growing (SRG) based image segmentation process homogeneous region depends on the image granularity features, where the interested structures with dimensions comparable to the speckle size are extracted. The shape and size of the growing regions depend on this look up table entries. The region merging after the region growing also suppresses the high frequency artifacts. The diagnosis process is done based on the intensity threshold variation obtained from the segmented portions of the image and size of the portions compared to that of the standard stone sizes (less than 2 mm absence of stone, 2-4 mm early stages and 5mm and above presence of kidney stones). Results: The parameters of texture values, intensity threshold variation and stones sizes are evaluated with experimentation of various Ultrasound kidney image samples taken from the clinical laboratory. The texture extracted from the segmented portion of the kidney images presented in our study precisely estimate the size of the stones and the position of the stones in the kidney which was not done in the earlier studies. Conclusion: The integrated improved SRG and classification mechanisms presented in this study diagnosis the kidney stones presence and absence along with the early stages of stone formation

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Study on characteristics of soil, to determine the types of crops suitable for cultivation in a particular region can increase the yield to greater extent, which minimizes the expenditures involved in irrigation and application of fertilizers. With the tested techniques available for calibrating the quality of soil and the crops suitable for cultivation in it, it is possible to determine the exact crop, irrigation patterns and even the cycle and quantity of fertilizer application. This paper dealt with the application of SOM based clustering and Artificial Intelligence techniques, to analyze the patterns of soils distributed across huge geographical area and identify the suitable types of crops for the particular soil. Estimation of exact crop(s) suitable for a particular region can help stave off redundant maintenance and the inherent expenditures that would occur due to over irrigation and over usage of fertilizers, to fulfill the natural deficiencies. Our Focus is to improve the optimal utilization of innate characteristics in a soil through cultivation of appropriate crops, which will increase the volume and quality of yield, in particular for a developing country like India, where the huge majority of the population depends primarily on agriculture for livelihood.

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