Medical Text and Image Processing

Author(s):  
Behzad Soleimani Neysiani ◽  
Hassan Homayoun
2018 ◽  
Vol Volume-2 (Issue-3) ◽  
pp. 379-381
Author(s):  
Prof. Vijay More ◽  
Ms. Ankita Shetty ◽  
Ms. Aishwarya Mapara | Mr. Rahul Ghuge | Mr. Rohit Sharma ◽  

2017 ◽  
Author(s):  
Ch Sudhakar ◽  
A Sravani ◽  
N. Thirupathi Rao ◽  
Debnath Bhattacharyya

1984 ◽  
Vol 4 (7) ◽  
pp. 12-22 ◽  
Author(s):  
Lars Blomberg ◽  
Kerstin Frenckner ◽  
Bjorn Kruse ◽  
Gunilla Lonnemark ◽  
Staffan Romberger ◽  
...  

2014 ◽  
Author(s):  
Shigeyuki Sakaki ◽  
Yasuhide Miura ◽  
Xiaojun Ma ◽  
Keigo Hattori ◽  
Tomoko Ohkuma

The processing of medical image has encountered sensational development, and its researching is doing by almost every field of engineering or medical sciences like designing, insights, material science, science and medication. CADxprocessing has recently transformed into a critical bit of clinical day by day practice. Joined by a flood of new headway of high advancement and use of various imaging modalities, more challenges develop; for example, how to process and separate a basic volume of images with the objective that splendid information can be conveyed for ailment ends and treatment. Thusly, the inside steps of image examination, to be explicit: include extraction, division, order, quantitative estimations, and translation are displayed in sperate portions. Because of its high importance, the attention is on division of biomedical image. Remarkable division methodologies and strategies have been made in the medical application zone. The principle goals of this paper are to give a preamble to crucial thoughts and frameworks for medicinal image taking care of and to propel interests for further assessment and research in medical imaging handling. We will display the Medical Image Processing and layout related research work around there.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Pradeep Niroula ◽  
Yunseong Nam

AbstractAlgorithms that search for a pattern within a larger data-set appear ubiquitously in text and image processing. Here, we present an explicit, circuit-level implementation of a quantum pattern-matching algorithm that matches a search string (pattern) of length M inside a longer text of length N. Our algorithm has a time complexity of $$\tilde{O}(\sqrt{N})$$ O ̃ ( N ) , while the space complexity remains modest at O(N + M). We report the quantum gate counts relevant for both pre-fault-tolerant and fault-tolerant regimes.


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