scholarly journals Identifying Deviations in Microscopic Blood Images using Parallel Computing and Divide and Conquer Image Fragmentation

2020 ◽  
pp. 54-59
Author(s):  
Sudhir Tirumalasetty ◽  
J. Sri Latha ◽  
J. Neeharika ◽  
L. Sri Pravallika ◽  
M. Manasa
Keyword(s):  
Parallel Computing ◽  
Ct Scan ◽  
Shortest Path ◽  
Medical Images ◽  
Specific Area ◽  
Divide And Conquer ◽  
Shortest Path Algorithm ◽  
Microscopic Images ◽  
Patient Diagnosis ◽  
Fungal Identification

Most of the patient diagnosis revolves around in identifying abnormalities in their respective medical images. These images are of various types, likely Ultrasound, CT scan, MRI and microscopic images like bio-chemical slides, micro-biological slides & pathological slides. Few abnormalities are fractures, bad cells in blood, tumors, fungal identification etc. Finding the abnormal portions in these images needs expertise by the physician; this apt identification promotes and guarantees healthy medication by the physician or surgeon to patient. In medical microscopic images normal portions and abnormal portions are mixed together. None of the abnormal portions are related to abnormal and normal portions of image i.e. deviations are scattered among normal portions of image. These deviations are not present in some portions for specific area in the images. None of these deviations are overlapped nor can be grouped together into a single portion physically in the image. Deviations are isolated along with normal portions of images. Identifying such deviations is vital. In previous methods these deviations are identified used BFS and Shortest Path Algorithm. This paper focuses on identifying deviations using parallel computing applied over fragmented portions of blood images using divide and conquer.

scholarly journals Identifying and Grouping Abnormalities in Medical Images using Shortest Path Algorithms

2019 ◽  
Vol 9 (2) ◽  
pp. 4908-4913
Keyword(s):  
Ct Scan ◽  
Hierarchical Clustering ◽  
Shortest Path ◽  
Medical Images ◽  
Shortest Path Algorithms ◽  
Path Calculation

The majority of the patient conclusion rotates around in distinguishing variations from the norm in their particular restorative pictures. These pictures are of different kinds, likely Ultrasound, CT Scan, MRI and infinitesimal pictures like bio-synthetic slides, smaller scale organic slides and neurotic slides. Barely any irregularities are cracks, awful cells in blood, tumors, contagious recognizable proof and so on. Finding the unusual segments, abnormalities in these pictures needs aptitude by the doctor; this adept recognizable proof advances and ensures sound drug by the doctor or specialist to persistent. In medicinal infinitesimal pictures ordinary bits and strange segments are combined. None of the irregular segments are identified with strange and typical parts of picture for example deviations are dissipated among ordinary bits of picture. These deviations are absent in certain bits for explicit region in the pictures. None of these deviations are covered nor can be gathered into a solitary segment physically in the picture. Deviations can be segregated alongside typical segments of pictures. Recognizing such deviations incompletely goes under bunching. This venture recognizes deviations in Medical Microscopic pictures. These deviations can be distinguished outwardly which uncovers about the nearness of deviation however to know the level of deviation in an example picture is basic. So as to accomplish this all deviations must be associated. This task interfaces all deviations utilizing Shortest Path calculation and bunches utilizing Hierarchical Clustering calculations.

Utilizing Restricted Direction Strategy and Binary Heap Technology to Optimize Dijkstra Algorithm in WebGIS

2009 ◽  
Vol 419-420 ◽  
pp. 557-560 ◽  
Author(s):  
Rui Li
Keyword(s):  
Shortest Path ◽  
Operating Efficiency ◽  
Dijkstra Algorithm ◽  
Shortest Path Algorithm ◽  
Research Focus ◽  
Network Information ◽  
The Core ◽  
Highway Network ◽  
Core Issue ◽  
Storage Structures

Shortest path is the core issue in application of WebGIS. Improving the efficiency of the algorithm is an urgent requirement to be resolved at present. By the lossy algorithm analyzing, which is the current research focus of the shortest path algorithm to optimize, utilizing adjacency table of storage structures, restricted direction strategy and binary heap technology to optimize the algorithm, thereby reduce the scale of algorithm to improve the operating efficiency of algorithm. This scheme has been applied in the simulation of the data downloaded from the Guangdong Provincial Highway Network Information System and satisfactory results have been obtained.

scholarly journals Shortest path algorithm for optimal sectioning of hydrocarbon transport pipeline

2016 ◽  
Vol 49 (12) ◽  
pp. 532-537
Author(s):  
A. Cano-Acosta ◽  
John Fontecha ◽  
Nubia Velasco ◽  
Felipe Muñoz-Giraldo
Keyword(s):  
Shortest Path ◽  
Shortest Path Algorithm ◽  
Hydrocarbon Transport
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