Automatic scanning of Malaria infected blood slide images using Mathematical Morphology

2002 ◽  
Author(s):  
K.N.R.M. Rao
Keyword(s):  
Mathematical Morphology ◽  
Infected Blood ◽  
Blood Slide ◽  
Automatic Scanning

Bacterial Shock due to Transfusion with Yersinia enterocolitica Infected Blood

1984 ◽  
Vol 16 (4) ◽  
pp. 411-412
Author(s):  
Gunnar Bjune ◽  
Tom Erik Ruud ◽  
Jan Eng
Keyword(s):  
Yersinia Enterocolitica ◽  
Infected Blood

Applications of Mathematical Morphology to Range Imagery

1987 ◽  
Author(s):  
Thomas R. Esselman ◽  
Jacques G. Verly
Keyword(s):  
Mathematical Morphology

Induction of Haemolysis and DNA Fragmentation in a Normal and Malarial-Infected Blood by Commonly - used Antimalarial Drugs in the North-Western Region of Nigeria

2016 ◽  
Vol 10 (1) ◽  
pp. 49-55 ◽  
Author(s):  
Aliyu Muhammad ◽  
Mohammed Ibrahim ◽  
Ochuko Erukainure ◽  
Nathan Habila ◽  
Aimola Idowu ◽  
...  
Keyword(s):  
Dna Fragmentation ◽  
Antimalarial Drugs ◽  
Western Region ◽  
Infected Blood ◽  
The North ◽  
North Western

scholarly journals Modeling Imprecise and Bipolar Algebraic and Topological Relations using Morphological Dilations

2021 ◽  
Vol 5 (1) ◽  
pp. 1-20
Author(s):  
Isabelle Bloch
Keyword(s):  
Information Processing ◽  
Fuzzy Sets ◽  
Mathematical Morphology ◽  
Complete Lattice ◽  
Spatial Reasoning ◽  
Topological Relations ◽  
Preference Modeling ◽  
Logical Sense ◽  
Bipolar Fuzzy Sets ◽  
Core Features

Abstract In many domains of information processing, such as knowledge representation, preference modeling, argumentation, multi-criteria decision analysis, spatial reasoning, both vagueness, or imprecision, and bipolarity, encompassing positive and negative parts of information, are core features of the information to be modeled and processed. This led to the development of the concept of bipolar fuzzy sets, and of associated models and tools, such as fusion and aggregation, similarity and distances, mathematical morphology. Here we propose to extend these tools by defining algebraic and topological relations between bipolar fuzzy sets, including intersection, inclusion, adjacency and RCC relations widely used in mereotopology, based on bipolar connectives (in a logical sense) and on mathematical morphology operators. These definitions are shown to have the desired properties and to be consistent with existing definitions on sets and fuzzy sets, while providing an additional bipolar feature. The proposed relations can be used for instance for preference modeling or spatial reasoning. They apply more generally to any type of functions taking values in a poset or a complete lattice, such as L-fuzzy sets.

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