scholarly journals Medical Image Processing in the Age of Deep Learning - Is There Still Room for Conventional Medical Image Processing Techniques?

2017 ◽  
Author(s):  
Jason Hagerty ◽  
R. Joe Stanley ◽  
William V. Stoecker
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Medical Image ◽  
Medical Image Processing ◽  
Image Processing Techniques ◽  
Processing Techniques

scholarly journals Breast histopathological image analysis using image processing techniques for diagnostic puposes: A methodological review

2021 ◽  
Vol 46 (1) ◽  
Author(s):  
R Rashmi ◽  
Keerthana Prasad ◽  
Chethana Babu K Udupa
Keyword(s):  
Breast Cancer ◽  
Image Processing ◽  
Medical Image ◽  
Human Life ◽  
Medical Image Processing ◽  
Histopathological Analysis ◽  
Image Processing Techniques ◽  
Computer Aided ◽  
Histopathological Images ◽  
Processing Techniques

AbstractBreast cancer in women is the second most common cancer worldwide. Early detection of breast cancer can reduce the risk of human life. Non-invasive techniques such as mammograms and ultrasound imaging are popularly used to detect the tumour. However, histopathological analysis is necessary to determine the malignancy of the tumour as it analyses the image at the cellular level. Manual analysis of these slides is time consuming, tedious, subjective and are susceptible to human errors. Also, at times the interpretation of these images are inconsistent between laboratories. Hence, a Computer-Aided Diagnostic system that can act as a decision support system is need of the hour. Moreover, recent developments in computational power and memory capacity led to the application of computer tools and medical image processing techniques to process and analyze breast cancer histopathological images. This review paper summarizes various traditional and deep learning based methods developed to analyze breast cancer histopathological images. Initially, the characteristics of breast cancer histopathological images are discussed. A detailed discussion on the various potential regions of interest is presented which is crucial for the development of Computer-Aided Diagnostic systems. We summarize the recent trends and choices made during the selection of medical image processing techniques. Finally, a detailed discussion on the various challenges involved in the analysis of BCHI is presented along with the future scope.

scholarly journals A Research on Automation Diagonsis of Pattern Recognition in Stained HEP-2 Cells

2019 ◽  
Vol 8 (11S2) ◽  
pp. 337-345
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Medical Image ◽  
Medical Image Processing ◽  
High Variability ◽  
Image Processing Techniques ◽  
Advantages And Disadvantages ◽  
Initial Work ◽  
Diagnosis Method ◽  
Processing Techniques

Diagnosis of autoimmune diseases can be achieved via Indirect Immunofluorescence (IIF) images using human epithelial (HEp-2) cell as substrate in laboratory. The automation of this diagnosis method is still challenging because of using various liquids to fix the HEp-2 cells in the slides. Due to various fixation methods, nuclear morphology of cell suffers high variability. This survey reviews all the difficulties in the analysis and recognition of pattern recognition and surveys various image processing techniques which leads to the automation diagnosis. This work consist of advantages and disadvantages of various procedures. Eventually, comparison of their corresponding results are presented. I assure that this initial work may attract many medical image processing researchers to enter into this field.

scholarly journals A review on analysis and diagnosis of diseases like tumor using medical image processing techniques

2020 ◽  
Author(s):  
Arachana Khandait ◽  
Ashish Panat ◽  
Ashish Panat
Keyword(s):  
Image Processing ◽  
Image Quality ◽  
Medical Image ◽  
Image Quality Assessment ◽  
Processing System ◽  
Medical Image Processing ◽  
Dynamic Monitoring ◽  
Challenging Problem ◽  
Image Processing Techniques ◽  
Processing Techniques

The field of image processing, image quality assessment is a fundamental and challenging problem with many interests in a variety of applications. Dynamic monitoring, adjusting image quality, optimizing algorithms and parameter settings of image processing systems are benchmarking in image processing system and algorithms. In this paper using such techniques we are going to analysis the detection of diseases like tumour for the ease in medical use.

Quantum Computation Perspectives in Medical Image Processing

2010 ◽  
Vol 2 (2) ◽  
pp. 16-46
Author(s):  
Pedro Rodrigues ◽  
Manuel João Ferreira ◽  
João Luís Monteiro
Keyword(s):  
Image Processing ◽  
Quantum Computation ◽  
Computational Methods ◽  
Medical Image ◽  
Functional Performance ◽  
Digital Images ◽  
Medical Image Processing ◽  
Quantum Devices ◽  
Image Processing Techniques ◽  
Processing Techniques

The need to increase the complexity of computational methods to produce improvements in functional performance, particularly in medical image processing applications, leads to find suitable physical devices. This chapter describes two ways of adapting the techniques of image processing to quantum devices. This kind of computing can achieve, for some problems, unparalleled performance as compared to classic computing. In the first method, using the quantum Grover’s algorithm how to implement image processing techniques under quantum rules is shown. In the second method, using diffraction and interference, the possibility of using less complex quantum devices for processing digital images is treated. Using leucocytes images, that mode is tested.

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