Sara Noor Eldin, Jana Khaled Hamdy, Ganna Tamer Adnan, Maysoon Hossam, Dr Ammar Mohammed, Eng Noha Elmasry, and Eng Menna Gamil
Cancer is the second-highest cause of death as reported by the World Health Organization. A correct diagnosis of Breast Cancer ensures that appropriate treatment plans and procedures are provided to patients. Due to the disparity in the pathologists’ skills, manual histopathology examinations conducted by them are complex, time-intensive, and might be vulnerable to misinterpretations. Using Deep Learning algorithms, the key concept of our proposed system is to diagnose breast cancer types from microscopy biopsy images. The proposed system will detect whether the abnormal lesions presented in these images are benign or malignant and if it is malignant, it will be stated if it is an In-Situ Carcinoma or Invasive Carcinoma. We seek to reduce the time results taken to reach patients who are in both physical and emotional distress, as well as reducing the possibility of misdiagnosis that might lead to more severe complications in patients’ lives.
The goal of the Software Design Description document is to record design information in order to represent the software design. It is also the key to communicating with design stakeholders. It will provide a detailed description of the system architecture and design, as well as a review of the requirements and an overview of the system for the team.
The purpose of the Software Design Document is to promote software development by providing a fully describable design of the system. Not only a defined method of how the system is designed and planned to be developed but also important details for the software and system being built.
The Software design document will describe in details the architecture of the Breast Cancer Diagnosis System. The first section is the introduction which will discuss the document’s purpose, scope, and overview. In the second section, we will talk about the systems overview, scope, goals, and timeline. In the third section, the system’s design viewpoints are discussed. It includes the following (context, composition, logical, patterns use, algorithm, interaction, and interface viewpoint). While in the fourth section; the Data Design consists of data, dataset, and database design description. The fifth section; the Human Interface Design, includes user interface and screen images. Finally, the sixth section includes a requirements matrix, which is a table that describes the system’s functions and status.
1.4 Intended audience
The project team is the one that is charged with this document in order to monitor the project. The stakeholders that can benefit from this system are patients, pathologists, and hospitals.