The objective of any software development is to deploy quality product with zero defects by meeting the end user expectations. There are several Software Development Life Cycle methodologies being followed to achieve this and the selection of best methodology is circumstance dependent. With our experience using Lean and Agile principles since last 4 years, in this paper we would like to explain in detail with statistics that these principles and practices can be successfully implemented in a iterative model development SDLC to achieve the matured, quality software in a long term medical imaging product. We will prove that it has positive impact on the software quality by comparing the outcome after following Lean and Agile principles with the prior results where traditional waterfall method was followed.

Today's world is very much dependent on the web applications, may it be shopping or financial transactions. Providing security to these web applications isvery important. Most of the transactioninformation or the customer information is stored in the backend databases for these web applications. One of the vulnerabilities of these web applications is SQL (Structured Query Language) injection attack. Also, the web application sessions are prone to session hijacking attack, if the adversary can get hold of the session id. Considering that there are various tools available to retrieve session/HTTP cookies, this makes web applications very vulnerable session hijacking attacks. Though there are many ways proposed to defend the databases against SQL injection attacks, there is no sure shot way to prevent these SQL injection attacks. This project proposes an efficient technique for the prevention of SQL injection attack and session hijacking. The hashing technique is used for implementing the preventionthese attacks.

The use of magnetic resonance (MR) Image has become more significant when treating rectal cancer. Rectal cancer can be staged more accurately with MRI, which serves as a great tool for choosing the most suitable course of action. Image pre-processing is used to improve the quality of image and making it better for analysis and further processing. The study carried out in this paper is concentrated on pre-processing methods like Gaussian and Sobel filtering. The filtering techniques were implemented on Pelvic MR images obtained from Kasturba Medical College (KMC), Manipal. The findings suggest that Sobel filtering had a superior output image quality, indicating its potential as a preferred preprocessing technique for enhancing Pelvic MR images in rectal cancer diagnosis and treatment planning. The output image efficiency is calculated by Peak to Signal Noise Ratio (PSNR) and Mean Square Error (MSE).

Background: The purpose of the research was to improve the polyp detection accuracy in CT Colonography (CTC)through effective colon segmentation, removal of tagged fecal matter through Electronic Cleansing (EC), and measuringthe smaller polyps. Methods: An improved method of boundary-based semi-automatic colon segmentation with theknowledge of colon distension, an adaptive multistep method for the virtual cleansing of segmented colon based onthe knowledge of Hounsfield Units, and an automated method of smaller polyp measurement using skeletonizationtechnique have been implemented. Results: The techniques were evaluated on 40 CTC dataset. The segmentationmethod was able to delineate the colon wall accurately. The submerged colonic structures were preserved withoutsoft tissue erosion, pseudo enhanced voxels were corrected, and the air-contrast layer was removed without losingthe adjacent tissues. The smaller polyp of size less than validated qualitatively and quantitatively. Segmented colons were validated through volumetric overlap computation,and accuracy of 95.826±0.6854% was achieved. In polyp measurement, the paired t-test method was applied to comparethe difference with ground truth and at α=5%, t=0.9937 and p=0.098 was achieved. The statistical values of TPR=90%,TNR=82.3% and accuracy=88.31% were achieved. Conclusion: An automated system of polyp measurement has beendeveloped starting from colon segmentation to improve the existing CTC solutions. The analysis of domain-basedapproach of polyp has given good results. A prototype software, which can be used as a low-cost polyp diagnosis tool,has been developed.