Medical image retrieval for augmenting diagnostic radiology

Even though the use of medical imaging to diagnose patients is ubiquitous in clinical settings, their interpretations are still challenging for radiologists. Many factors make this interpretation task difficult, one of which is that medical images sometimes present subtle clues yet are crucial for diagnosis. Even worse, on the other hand, similar clues could indicate multiple diseases, making it challenging to figure out the definitive diagnoses. To help radiologists quickly and accurately interpret medical images, there is a need for a tool that can augment their diagnostic procedures and increase efficiency in their daily workflow. A general-purpose medical image retrieval system can be such a tool as it allows them to search and retrieve similar cases that are already diagnosed to make comparative analyses that would complement their diagnostic decisions. In this thesis, we contribute to developing such a system by proposing approaches to be integrated as modules of a single system, enabling it to handle various information needs of radiologists and thus augment their diagnostic processes during the interpretation of medical images. We have mainly studied the following retrieval approaches to handle radiologists’different information needs; i) Retrieval Based on Contents, ii) Retrieval Based on Contents, Patients’ Demographics, and Disease Predictions, and iii) Retrieval Based on Contents and Radiologists’ Text Descriptions. For the first study, we aimed to find an effective feature representation method to distinguish medical images considering their semantics and modalities. To do that, we have experimented different representation techniques based on handcrafted methods (mainly texture features) and deep learning (deep features). Based on the experimental results, we propose an effective feature representation approach and deep learning architectures for learning and extracting medical image contents. For the second study, we present a multi-faceted method that complements image contents with patients’ demographics and deep learning-based disease predictions, making it able to identify similar cases accurately considering the clinical context the radiologists seek. For the last study, we propose a guided search method that integrates an image with a radiologist’s text description to guide the retrieval process. This method guarantees that the retrieved images are suitable for the comparative analysis to confirm or rule out initial diagnoses (the differential diagnosis procedure). Furthermore, our method is based on a deep metric learning technique and is better than traditional content-based approaches that rely on only image features and, thus, sometimes retrieve insignificant random images

Knowledge and strategies of controlling plagiarism at the University of Dar es Salaam, Tanzania

This paper presents findings of a study conducted at the University of Dar es Salaam (UDSM) Tanzania concerning academic staff and students’ knowledge of plagiarism. The study investigated forms of plagiarism practiced and prevention strategies used. Questionnaires were used to collect data from students and academic staff. In contrast to academic staff, students were found to have insufficient knowledge on plagiarism despite the existence of various strategies for awareness creation on the problem. The results study has revealed various plagiarism forms practiced at the University, as well as prevention measures used. The study ends with a set of strategies to control plagiarism, in addition to e existing initiatives

Short communications: The first confirmed breeding record and new distribution data for Böhm’s Flycatcher Myopornis boehmi in Tanzania

No abstrac

Preliminary observations on the avifauna of Ikokoto Forest, Udzungwa Mountains, Tanzania

A study was conducted at c. 110 ha of Ikokoto forest using mist-netting and general field observations. Sixty-four species were recorded of which 61% were of conservation importance in terms of forest dependence. All species were found to belong to the familiar assembly of the large Udzungwa forests. Six species, the Green-throated Greenbul Andropadus fusciceps, Spot-throat Modulatrix stictigula, African Tailorbird Artisornis metopias, Black-lored Cisticola Cisticola nigriloris, Uhehe Fiscal Laniarius marwitzi and Fülleborn’s Black Boubou Laniarius fuelleborni detected are restricted range and one species Moreau’s Sunbird Nectarinia moreaui is nearthreatened according to IUCN threat status. The presence of many species which are forest dependent in this tiny forest indicates that this site, though small in size and highly fragmented, retains significant conservation value for birds

Analysis of Occupational Health and Safety in Construction Industry in Tanzania

Construction practitioners’ world – wide are increasingly becoming aware that they cannot concentrate primarily on the technical aspects of the industry alone and ignoring the workers and others who may be adversely affected by construction activities. In most developing countries, including Tanzania, safety consideration in the construction project delivery is not given a high priority. The current approach is that safety interventions occur in response to specific, often major accidents or injury. The main objective of this research is to scrutinize why road and building construction industries in Tanzania have paid little attention to the issues of health and safety in construction sites. Data was obtained from different literatures and fields. Secondary data collected from different sources including publication on health and safety, academic journals, books, official documents and reports from Government Ministries, Agencies, NGO’s and development partners. Conclusively people pay little attention to the things concerning health and safety issues in construction building sites. The absence of clear national health and safety policy to safeguard all issues regarding the welfare of the construction workers in the country is a challenge. The fact is construction industry is still suffering on how health and safety would be safely practiced in construction sites. So, we need to make a clear policy concerning health and safety in general with regards to the construction industry. Also training on health and safety to all stakeholders should be taken into account as well as introduction of safety gears to the workers on the field of construction building sites

Economics of rainwater harvesting for crop enterprises in semi-arid areas: the case of Makanya Watershed in Pangani River Basin, Tanzania

River basinsWatershedsRainWater harvestingVillagesMaizeBeansRunoff

Protection against unfair dismissal of employees living with HIV/AIDS in the workplace: a comparative study

No abstract availableJurisprudenceLL.M

Economics of rainwater harvesting for crop enterprises in semi-arid areas: the case of Makanya Watershed in Pangani River Basin, Tanzania

River basinsWatershedsRainWater harvestingVillagesMaizeBeansRunoffEconomic aspects

Use of a hydrological model for environmental management of the Usangu Wetlands, Tanzania

Wetlands / Rivers / Ecology / Environmental effects / Remote sensing / Hydrology / Simulation models / Water budget / Irrigated sites / Land cover / Time series analysis / Tanzania / Usangu Wetlands / Great Ruaha River

Agriculture is the main driver of deforestation in Tanzania

Reducing deforestation can generate multiple economic, social and ecological benefits by safeguarding the climate and other ecosystem services provided by forests. Understanding the relative contribution of different drivers of deforestation is needed to guide policies seeking to maintain natural forest cover. We assessed 119 randomly selected plots from areas deforested between 2010 and 2017, in Tanzania. Through ground surveys and stakeholder interviews we assessed the proximate deforestation drivers at each point. Crop cultivation was the most commonly observed driver occurring in 89% of plots, compared to livestock grazing (69%) and charcoal (35%). There was evidence of fire in 77% of plots. Most deforestation events involved multiple drivers, with 83% of plots showing signs of two or more drivers. Stakeholder interviews identified agriculture as the primary deforestation driver in 81% of plots, substantially more than charcoal production (12%), timber harvesting (1%) and livestock (1%). Policy-makers in Tanzania have sought to reduce deforestation by reducing demand for charcoal. However, our work demonstrates that agriculture, not charcoal, is the main driver of deforestation in Tanzania. Beyond protected areas, there is no clear policy limiting the conversion of forests to agricultural land. Reducing deforestation in Tanzania requires greater inter-sectoral coordination between the agriculture, livestock, land, energy and forest sectors