Histopathological image analysis is a specialised area of medical imaging that involves the careful examination and interpretation of tissue samples to diagnose and investigate diseases. We begin by reviewing the traditional methods of histopathological image analysis and their limitations, setting the stage for the necessity of computational approaches. The study then delves into the core components of computer-assisted analysis, including preprocessing techniques, feature extraction, and classification algorithms. Preprocessing steps such as staining normalization, noise reduction, and image segmentation are critical for preparing raw images for further analysis. Feature extraction methods, ranging from handcrafted features to DL based features, are discussed in detail, emphasizing their role in capturing relevant tissue characteristics. The classification stage employs various machine learning models, including SVM, RF, and NN, with a focus on CNN due to their superior performance in image recognition tasks. 

Computer-Assisted Analysis of Histopathological Images

This paper discusses about recommendations of the movies. A movie recommendation system is beneficial for entertaining quotient. This system suggests movies to users based on user’s interest, movie’s popularity. It narrows down the database of information and helps users in finding their appropriate need or interest in movies. A recommendation is an abstract of information that filters the data on the basis on "ratings" or "preferences". They are widely used in all sorts of movie platforms like Netflix, amazon prime video etc.

A Recommendation System to Envision Movie Ranking Using Collaborative Filtering

In the paper, we have described the overall experience and outcome of creating a tool architecture capable of potentially giving lakhs of students with real time hands-on learning experience in Cyber security field using scripts and their functioning. Creating a tool with different scripts performing specific task at hand to give students knowledge of scripting in not only one specific method, but diversify their knowledge in the field. This tool basically helps to create their own understanding in the field of cyber security, and give a step ahead from only theoretical knowledge from books. Reading the backend of a script from a book and seeing them work in real creates a huge difference which is covered in this tool.

The Scripter: A Tool for Penetration Testing

In the paper, we have described the overall experience and outcome of creating a tool architecture capable of potentially giving lakhs of students with real time hands-on learning experience in Cyber security field using scripts and their functioning. Creating a tool with different scripts performing specific task at hand to give students knowledge of scripting in not only one specific method, but diversify their knowledge in the field. This tool basically helps to create their own understanding in the field of cyber security, and give a step ahead from only theoretical knowledge from books. Reading the backend of a script from a book and seeing them work in real creates a huge difference which is covered in this tool. 

Medical Record Management System Using Blockchain Technology

Recent trends with Histopathological imagery led to rapid progress towards quantifying the perceptive issues, while prognostic, due to subjective variability among readers. This variability leads to distinguished prognosis reports and generates variability in treatment as well. Latest advancements in image analysis tools have allowed the powerful computer-assisted diagnostic system to assist oncologist in their diagnosis process on radiological data. In this study, we present a thoughtful analysis of texture heterogeneity and morphological characteristic on various lymphomas like Follicular, Neuroblastoma, Breast, and Prostate tissue images for classifying them into respective grades. The study presents a systematic survey of the computational steps of these Lymphomas, which includes recent scenario of diagnosis process to classify these lymphomas into respective grades along with its limitations, followed by it shows the pre-requisite of the computer-assisted diagnosis system and finally explains various segmentation techniques based on image descriptor and subsequent classification of biopsy into respective grades. This paper reviews recent state of the art technology i.e. Computer Assisted Diagnosis (CAD) for Histopathology and also briefly describes the recent development in histology and its application towards quantifying the perceptive issue in the domain of histopathology being pursued in the United State and India.

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Study of Computerized Segmentation & Classification Techniques: An Application to Histopathological Imagery

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Study of Computerized Segmentation & Classification Techniques: An Application to Histopathological Imagery