Master of Engineering - ME (Medical Software) This program has been designed to create skilled professionals who can engineer the medical world. Students are trained to suit the industry requirements. The curriculum is jointly designed in consultation with experts from GE Health Care, Professors from leading educational institutions. Students are trained to suit the industry requirements. Program Highlights: 1. Practical: All the subjects are associated with lab to provide the practical knowledge. 2. Mini Project: Two Mini Projects during the program. In this students are expected to select a problem in the area of their interest and implement in hardware / software. 3. Seminar: Two Seminars during the program. In this students have to select a latest topic and make a literature survey in the area of their interest and present. 4. Project: Internship will be carried out at the Industry/ Institution for 10 to 12 months. Semester - I Semester - II Data Structures & Algorithms Advanced Image Processing Software Engineering Dot Net Technologies Computer Networks Mobile Application Development using Android Medical Imaging Elective 1 Database Programming in Java Elective 2 Elective subject details Elective - 1 Elective - 2 Bio Medical Signal Processing Data Mining Computer Graphics Enterprise Computing I Human Computer Interaction Neural Networks & Fuzzy Logic Design Patterns & Coding Conventions Computer Vision Bio-Instrumentation IT Project Management Real Time Operating System System Software Information Storage and Management Enterprise Computing II Cryptography & Network Security Digital Speech Processing Knowledge Management Time-Frequency & Wavelet Transforms Network Management Pattern Recognition Web Application Development Semester III & IV Internship / Project work for 10-12 months in Industry / Research Organization / University.
Brief Syllabus Semester - I 1. Data Structures and Algorithms Algorithm Analysis Techniques; Elementary data structures; Sorting & Searching Techniques; Operations on Sets; Trees; Graphs; Algorithm Design Techniques ; NP-Hard and NP-Complete Problems. 2. Software Engineering Intro to SE and concepts; Software Processes; Software Req. Analysis & Specifications; Analysis Modeling Software Design Concepts & Principles; Software Implementation; Software Testing; Documentation Requirements. 3. Computer Networks Computer Networks; Communication Devices; Fundamentals of data communication; Internet addresses; Routing Algorithms; Congestion control algorithms; Internet Transport protocols (TCP & UDP), SMTP, DHCP, DNS, Client ; Applications; Digital Voice & Video, VOIP; ATM; Wireless networks. 4. Medical Imaging X rays: Ultrasound: Radionuclide imaging: MRI: DICOM: PACS: Digital Image Fundamentals: Image Enhancement. 5. Database Programming in Java Introduction to Java; Classes in java; Inheritance; Packages; Interfaces; I/O API s; Exception Handling; Java Applets, Applications ; Introduction to Swing; Introduction to Database concepts; SQL; Introduction to JDBC. Semester - II 1. Advanced Image Processing Image Segmentation and registration: Image representation and description: Image Compression: Pattern Recognition: Classifiers: Fuzzy Logic: Image Compression: Real-time Image processing architectures. 2. Dot Net Technologies Introducing C# and the.net Platform: The C# Programming Language: Programming with the.net Libraries: Web Applications and XML Web Services. 3. Mobile Application Development using Android Android building blocks; Android Screen UI Components; Data management with SQLite; Advanced topics; Adapters, background threads, Notifications, Location based services, Mapping, network connectivity services, telephony services. 4. Elective I 5. Elective - II Elective - I
1. Biomedical Digital Signal Processing Biomedical Signals; Digital Signal Processing; Adaptive Filters; BDSP Applications - Cardiological Signals, Neurological Studies, ECG Noise Cancellation, Data Reduction Technique. 2. Data Mining Core Topics; Advanced Topics; Web Mining; Spatial Mining; Temporal Mining; Security issues in Data mining. 3. Computer Graphics Line drawing algorithms ; 2-D transformations; Windowing -Viewport transformations; Clipping algorithms; 3-D transformations; 3-D projections;3-d clipping; Hidden line and hidden surface removal algorithms; Illumination; Phong shading; Polygon filling. 4. Enterprise Computing Characteristics of Enterprise Computing, Introduction to TSO & ISPF, Basic Application Programming, Introduction to SPUFI, 5. Human Computer Interaction The History of Interaction, Preliminaries, Designability of processes, Socio-organizational Approaches. 6. Neural Networks & Fuzzy Logic Neural Networks, Classifiers, Associative Memories, Fuzzy Logic, Linguistic variables and fuzzy IF- THEN rules, Fuzzy rule base and fuzzy inference engine, Fuzzifiers and defuzzifiers. 7. Design Patterns & Coding Conventions Design Patterns, Coding Conventions, Introduction, Names, Documentation, Complexity Management, Classes, Process, Formatting, Exceptions, Templates and Namespaces, Portability. 8. Computer Vision Image formation & Image models, Geometric camera models, Geometric camera calibration, Linear filters, Edge detection, Two views, Stereopsis, Mid level vision: Segmentation by clustering, High level vision: Finding templates using classifiers 9. Bio-Instrumentation Introduction, Study of therapeutic equipments, Study of Surgical devices, Medical Imaging Systems, X-ray Image Intensifiers, Pulse Oximetry. 10. IT Project Management Software Project Planning, Estimation, Project Schedules, Reviews, Software Requirements, Design and Programming, Software Testing. Using Project Management Effectively Understanding Change, Management and Leadership, Managing an Outsourced Project, Process Improvement. 11. Web Application Development Database concepts SQL, Programming_ASP.net, Web Services
Elective II 1. Real Time Operating System Introduction to OS and RTOS; Process Management; IPC using Shared Memory; IPC using Sockets; Multithreaded Programming; Process Scheduling; Synchronization; Deadlocks; Memory Management Strategies ; Virtual Memory Management; Overview of Real Time Systems, Real Time clocks and Real Time Scheduling Algorithms 2. System Software Assemblers; Loaders and linkers; Compilers - Lexical Analyzers, Context Free Grammars, Recursive Descent Parsing, Predictive Parsing, Bottom-up Parsing with LR(k) parsers; Intermediate Code; Introduction to code optimization 3. Information Storage & Management Storage devices & I/O Subsystems; Introduction to Networked Storage; Introduction to Information availability; EMC Products& tools A Case study; Storage Area Networks (SAN). 4. Enterprise Computing II Advanced JCL, Advanced Datasets, Understanding CICS. 5. Cryptography & Network Security CRYPTOGRAPHY - Some topics in Number theory, Classical Encryption Techniques, Block cipher and data encryption standard, Introduction to finite fields, Advanced encryption standard, Contemporary symmetric ciphers, Confidentiality using symmetric encryption, Public key encryption RSA, Key management, Message authentication and hash functions, Hash algorithms, Digital signature and authentication pr IP security otocols, NETWORK SECURITY PRACTICE - Authentication applications - Electronic mail security, IP Security, Web security. 6. Digital Signal Processing FFT Algorithms; Filter Structures, Design of FIR filters; Design of IIR Filters; Multirate Signal Processing; Adaptive Filters; DSP Processor 7. Knowledge Management The Knowledge Edge, From Information to Knowledge, Implementing Knowledge Management, Infrastructural Evaluation and Leverage The Leveraged Infrastructure: The Approach Aligning Knowledge Management and Business Strategy, The Second Phase: KM System Analysis, Design, and Development Infrastructural Foundations, Knowledge Audit and Analysis, Designing the KM Team, Developing the KM System, The Third Phase: KMS Deployment Prototyping and Deployment, The CKO and Reward Structures, The Final Phase and Beyond: Measuring ROI and Performance Metrics for Knowledge Work, Case Studies. 8. Time-Frequency and Wavelet Transforms Introduction to Wavelet transforms, Multi-resolution analysis and Continuous Wavelet Transform (Qualitative treatment), Discrete wavelet transform (DWT) (Qualitative treatment), Two-channel filter bank, Hands on with MATLAB Wavelet toolbox, Fourier Series and Geometry, Continuous wavelet transform (CWT), Discrete wavelet transform (DWT), Designing orthogonal wavelet systems, Discrete wavelet transform (DWT) and relation to filter banks, Generating and plotting of parametric wavelets, Biorthogonal wavelets. 9. Network Management
Introduction, SNMP v1, SNMP v2, SNMP v3, Network Management Functions, Remote Network Monitoring RMON 1, Remote Network Monitoring RMON 2, Management Tools, Systems and Applications. 10. Pattern Recognition Introduction, Statistical decision making, Syntactic Pattern Recognition, Supervised Learning, Nonparametric decision-making, Artificial Neural Networks.