Lymphatic Filariasis detection in microscopic images

Detalhes bibliográficos
Autor(a) principal: Rui Pedro Menezes da Rosa Neves
Data de Publicação: 2016
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/88914
Resumo: In Africa, the propagation of parasites like the lymphatic filariasis is complicating seriously the efforts of health professionals to cure certain diseases. Although there are medicines capable to treat the lymphatic filariasis, this needs to be discovered firstly which is not always an easy task having into account that in most countries affected by this disease it can only be detected at night (nocturne). The lymphatic filariasis is then, a parasitical infection which can originate changes or ruptures in the lymphatic system as well as an abnormal growth of certain areas of the body causing pain, incapacity and social stigma. Approximately 1.23 billion people in 58 countries from all over the world are threatened by this disease which requires a preventive treatment to stop its propagation which makes it even more important for the existence of a mechanism that is less costly and more agile in the analysis of a blood smear to verify the existence of microfilariae (little worms that are produced by other adult worms while housed in the lymphatic system). The lymphatic filariasis is caused by an infection with nematodes ("roundworms") of the Filariodidea family in which three types are inserted: Wuchereria Bancroft, responsible for 90% of all cases; Brugia Malayi, responsible for almost every remaining; B.Timori also causing the disease. All three have characteristics that can differentiate them which allow them to be identified. The current identification process of the disease consists on the analysis of microfilariae in a blood smear with a blood sample through a microscope and its identification by the observer. Taking this into account, it is intended to develop image analysis and processing techniques for the recognition and counting of the two principal types of filarial worms from a thin blood smear, a smartphone and a portable microscope making the detection possible without the need of a health professional and consequent automation of the process. To make this possible an adapter smartphone-microscope can be used to obtain an image with the magnification of 40x3. The images can then be analyzed in a server or in the smartphone, if it has enough processing for it. It is expected from this process that the need to resort to labs to process the blood smear gets fulfilled making the process more accessible and agile instead of costly and slow. For the detection of the parasites from the acquired images it is intended to implement, experiment and choose the more adequate operations. These comprise pre-processing operationswith the goal to enhance the acquired images and eliminate possible artifacts prevenient from the acquisition system. However, the principal operations should be those that allow the verification of existence or nonexistence, recognition and classification of the pretended parasites. Processing and analysis techniques that are common in these processes are based in the extraction of features (e.g. SIRF, SURF, and FLANN) template similarity, edge detection and description of contours and recognition of statistical patterns. Once detected and recognized one or more parasites and its types should be defined and used a rule to declare the presence of the disease and its stage.
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spelling Lymphatic Filariasis detection in microscopic imagesEngenharia electrotécnica, electrónica e informáticaElectrical engineering, Electronic engineering, Information engineeringIn Africa, the propagation of parasites like the lymphatic filariasis is complicating seriously the efforts of health professionals to cure certain diseases. Although there are medicines capable to treat the lymphatic filariasis, this needs to be discovered firstly which is not always an easy task having into account that in most countries affected by this disease it can only be detected at night (nocturne). The lymphatic filariasis is then, a parasitical infection which can originate changes or ruptures in the lymphatic system as well as an abnormal growth of certain areas of the body causing pain, incapacity and social stigma. Approximately 1.23 billion people in 58 countries from all over the world are threatened by this disease which requires a preventive treatment to stop its propagation which makes it even more important for the existence of a mechanism that is less costly and more agile in the analysis of a blood smear to verify the existence of microfilariae (little worms that are produced by other adult worms while housed in the lymphatic system). The lymphatic filariasis is caused by an infection with nematodes ("roundworms") of the Filariodidea family in which three types are inserted: Wuchereria Bancroft, responsible for 90% of all cases; Brugia Malayi, responsible for almost every remaining; B.Timori also causing the disease. All three have characteristics that can differentiate them which allow them to be identified. The current identification process of the disease consists on the analysis of microfilariae in a blood smear with a blood sample through a microscope and its identification by the observer. Taking this into account, it is intended to develop image analysis and processing techniques for the recognition and counting of the two principal types of filarial worms from a thin blood smear, a smartphone and a portable microscope making the detection possible without the need of a health professional and consequent automation of the process. To make this possible an adapter smartphone-microscope can be used to obtain an image with the magnification of 40x3. The images can then be analyzed in a server or in the smartphone, if it has enough processing for it. It is expected from this process that the need to resort to labs to process the blood smear gets fulfilled making the process more accessible and agile instead of costly and slow. For the detection of the parasites from the acquired images it is intended to implement, experiment and choose the more adequate operations. These comprise pre-processing operationswith the goal to enhance the acquired images and eliminate possible artifacts prevenient from the acquisition system. However, the principal operations should be those that allow the verification of existence or nonexistence, recognition and classification of the pretended parasites. Processing and analysis techniques that are common in these processes are based in the extraction of features (e.g. SIRF, SURF, and FLANN) template similarity, edge detection and description of contours and recognition of statistical patterns. Once detected and recognized one or more parasites and its types should be defined and used a rule to declare the presence of the disease and its stage.2016-07-142016-07-14T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://hdl.handle.net/10216/88914TID:201319772engRui Pedro Menezes da Rosa Nevesinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T15:00:41Zoai:repositorio-aberto.up.pt:10216/88914Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:13:35.868086Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Lymphatic Filariasis detection in microscopic images
title Lymphatic Filariasis detection in microscopic images
spellingShingle Lymphatic Filariasis detection in microscopic images
Rui Pedro Menezes da Rosa Neves
Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
title_short Lymphatic Filariasis detection in microscopic images
title_full Lymphatic Filariasis detection in microscopic images
title_fullStr Lymphatic Filariasis detection in microscopic images
title_full_unstemmed Lymphatic Filariasis detection in microscopic images
title_sort Lymphatic Filariasis detection in microscopic images
author Rui Pedro Menezes da Rosa Neves
author_facet Rui Pedro Menezes da Rosa Neves
author_role author
dc.contributor.author.fl_str_mv Rui Pedro Menezes da Rosa Neves
dc.subject.por.fl_str_mv Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
topic Engenharia electrotécnica, electrónica e informática
Electrical engineering, Electronic engineering, Information engineering
description In Africa, the propagation of parasites like the lymphatic filariasis is complicating seriously the efforts of health professionals to cure certain diseases. Although there are medicines capable to treat the lymphatic filariasis, this needs to be discovered firstly which is not always an easy task having into account that in most countries affected by this disease it can only be detected at night (nocturne). The lymphatic filariasis is then, a parasitical infection which can originate changes or ruptures in the lymphatic system as well as an abnormal growth of certain areas of the body causing pain, incapacity and social stigma. Approximately 1.23 billion people in 58 countries from all over the world are threatened by this disease which requires a preventive treatment to stop its propagation which makes it even more important for the existence of a mechanism that is less costly and more agile in the analysis of a blood smear to verify the existence of microfilariae (little worms that are produced by other adult worms while housed in the lymphatic system). The lymphatic filariasis is caused by an infection with nematodes ("roundworms") of the Filariodidea family in which three types are inserted: Wuchereria Bancroft, responsible for 90% of all cases; Brugia Malayi, responsible for almost every remaining; B.Timori also causing the disease. All three have characteristics that can differentiate them which allow them to be identified. The current identification process of the disease consists on the analysis of microfilariae in a blood smear with a blood sample through a microscope and its identification by the observer. Taking this into account, it is intended to develop image analysis and processing techniques for the recognition and counting of the two principal types of filarial worms from a thin blood smear, a smartphone and a portable microscope making the detection possible without the need of a health professional and consequent automation of the process. To make this possible an adapter smartphone-microscope can be used to obtain an image with the magnification of 40x3. The images can then be analyzed in a server or in the smartphone, if it has enough processing for it. It is expected from this process that the need to resort to labs to process the blood smear gets fulfilled making the process more accessible and agile instead of costly and slow. For the detection of the parasites from the acquired images it is intended to implement, experiment and choose the more adequate operations. These comprise pre-processing operationswith the goal to enhance the acquired images and eliminate possible artifacts prevenient from the acquisition system. However, the principal operations should be those that allow the verification of existence or nonexistence, recognition and classification of the pretended parasites. Processing and analysis techniques that are common in these processes are based in the extraction of features (e.g. SIRF, SURF, and FLANN) template similarity, edge detection and description of contours and recognition of statistical patterns. Once detected and recognized one or more parasites and its types should be defined and used a rule to declare the presence of the disease and its stage.
publishDate 2016
dc.date.none.fl_str_mv 2016-07-14
2016-07-14T00:00:00Z
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TID:201319772
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