Recognizing Microscopic Structures: Dense Semantic Segmentation of Multiple Histopathological Classes using Fully Convolutional Neural Networks

In order to alleviate the financial burden on the healthcare sector as well as relax its employees’ workload, there is a need to introduce novel tools that automate some of the tasks that today are performed manually. Especially pathology poses a problem with few pathologists, demanding manual labour and unnecessary work on benign tissue. As a response, the DOGS project aims to develop a tool to automate or assist in Gleason grading of histopathological images from prostate biopsies. It is probable that such a tool would benefit from having access to individually segmented, pathologically relevant objects from the images. Moreover, considering recent advances in deep learning and its frequently impressive performance on various image analysis tasks, it is natural to approach this challenge from a deep learning perspective. This thesis proposes several fully convolutional neural networks to be used for dense semantic segmentation on histopathological images. The networks’ architectures are all initially based on already proven networks but are modified in various ways to achieve better performance. Being a supervised machine learning task, the ground truth required to train the network has been developed as a part of the thesis. The best-performing network obtained an accuracy of 79.71 % mean intersection over union and the networks presented plausibly equaled or outperformed state-of-the-art methods in nuclei segmentation. However, further work is deemed necessary for reaching adequate segmentation performance. Several suggestions for possible future directions of work are presented, as well as obstacles that have to be considered moving onwards.To make a significant dent in the issues the healthcare sector faces today in terms of costs and overextended employees, a great increase of viable automated tools will sooner or later be needed. For pathologists this is no different. However, the complexity and size of microscopy images makes automated analysis of them difficult. This thesis achieved promising and first-of-its-kind results in tackling the very underexplored challenge of recognizing several structures in microscopy images at once. By using a deep learning approach heavily inspired from a pair of popular artificial neural networks a score of 80 % mean IU was reached. The resulting networks are prospects for use in several different preprocessing steps in medical image analysis applications – possibly enabling or improving automated tools in the pathological field in the future

Mechanical behaviour of tear opening in injection moulded plastic tops

The tear opening study is conducted with an example from the Tetra Pak package industry, the Tetra Top package. The top of the package is constructed by a injection molded low density thermoplastic. The package is opened with a tear opening located on the top part. In order to make tear opening more versatile, studies how opening forces reacts upon material modifications and alternative geometry has been made. The vertical displacement of the ’drawstring’ (i.e. pull-bridge) concentrate the stress around the tear opening and the shallow pit (e.g. notch) located were the fracture is supposed to initiate. The fracture initiates and the package opens when sufficient force is applied to the pull-bridge. The object of this study is how new materials affects the opening force. An alternate tougher material will in all cases increase the opening force. Modified geometry is hence, necessary to decrease the opening force. Computational studies has shown that a alternate geometry can decrease the opening force with 56%

A Sound Approach Toward a Mobility Aid for Blind and Low-Vision Individuals

Reduced independent mobility of blind and low-vision individuals (BLVIs) cause considerable societal cost, burden on relatives, and reduced quality of life for the individuals, including increased anxiety, depression symptoms, need of assistance, risk of falls, and mortality. Despite the numerous electronic travel aids proposed since at least the 1940’s, along with ever-advancing technology, the mobility issues persist. A substantial reason for this is likely several and severe shortcomings of the field, both in regards to aid design and evaluation.In this work, these shortcomings are addressed with a generic design model called Desire of Use (DoU), which describes the desire of a given user to use an aid for a given activity. It is then applied on mobility of BLVIs (DoU-MoB), to systematically illuminate and structure possibly all related aspects that such an aid needs to aptly deal with, in order for it to become an adequate aid for the objective. These aspects can then both guide user-centered design as well as choice of test methods and measures.One such measure is then demonstrated in the Desire of Use Questionnaire for Mobility of Blind and Low-Vision Individuals (DoUQ-MoB), an aid-agnostic and comprehensive patient-reported outcome measure. The question construction originates from the DoU-MoB to ensure an encompassing focus on mobility of BLVIs, something that has been missing in the field. Since it is aid-agnostic it facilitates aid comparison, which it also actively promotes. To support the reliability of the DoUQ-MoB, it utilizes the best known practices of questionnaire design and has been validated once with eight orientation and mobility professionals, and six BLVIs. Based on this, the questionnaire has also been revised once.To allow for relevant and reproducible methodology, another tool presented herein is a portable virtual reality (VR) system called the Parrot-VR. It uses a hybrid control scheme of absolute rotation by tracking the user’s head in reality, affording intuitive turning; and relative movement where simple button presses on a controller moves the virtual avatar forward and backward, allowing for large-scale traversal while not walking physically. VR provides excellent reproducibility, making various aggregate movement analysis feasible, while it is also inherently safe. Meanwhile, the portability of the system facilitates testing near the participants, substantially increasing the number of potential blind and low-vision recruits for user tests.The thesis also gives a short account on the state of long-term testing in the field; it being short is mainly due to that there is not much to report. It then provides an initial investigation into possible outcome measures for such tests by taking instruments in use by Swedish orientation and mobility professionals as a starting point. Two of these are also piloted in an initial single-session trial with 19 BLVIs, and could plausibly be used for long-term tests after further evaluation.Finally, a discussion is presented regarding the Audomni project — the development of a primary mobility aid for BLVIs. Audomni is a visuo-auditory sensory supplementation device, which aims to take visual information and translate it to sound. A wide field-of-view, 3D-depth camera records the environment, which is then transformed to audio through the sonification algorithms of Audomni, and finally presented in a pair of open-ear headphones that do not block out environmental sounds. The design of Audomni leverages the DoU-MoB to ensure user-centric development and evaluation, in the aim of reaching an aid with such form and function that it grants the users better mobility, while the users still want to use it.Audomni has been evaluated with user tests twice, once in pilot tests with two BLVIs, and once in VR with a heterogenous set of 19 BLVIs, utilizing the Parrot-VR and the DoUQ-MoB. 76 % of responders (13 / 17) answered that it was very or extremely likely that they would want use Audomni along with their current aid. This might be the first result in the field demonstrating a majority of blind and low-vision participants reporting that they actually want to use a new electronic travel aid. This shows promise that eventual long-term tests will demonstrate an increased mobility of blind and low-vision users — the overarching project aim. Such results would ultimately mean that Audomni can become an aid that alleviates societal cost, reduces burden on relatives, and improves users’ quality of life and independence

Інноваційне управління новачками

Detta projekt har gått ut på att bygga en självbalanserande robot på två hjul som autonomt ska kunna köra 10-30 meter rakt fram, detektera en svart linje på marken och sedan stanna och fortsätta hålla balansen. Vi valde en cykelkonstruktion med en propellerbestyckad vinge för balansering. Två propellrar regleras av en PID-regulator med hjälp av signaler från en accelerometer och ett gyro. Framdriften sker med en DC-motor kopplad till framhjulet. En reflexionssensor används för detekteringen av den svarta linjen och hela framdrivningen styrs via IR-fjärrkontroll.The goal of this project was to build a self-balancing robot on two wheels that autonomously can drive 10-30 meters, detect a black line on the ground and then stop while still upholding balance. We chose a bike-like construction with a propeller-mounted wing for balancing. Two propellers are regulated by a PID-regulator aided by an accelerometer and a gyro. Propulsion is done by a DC-motor on the front wheel. A reflex sensor is used to detect the black line and the whole propulsion system is remote controlled by IR

You Need To Focus To Validate

Many research students find challenges when validating their research. Especially when they have expectations to contribute to both practice and the research body of knowledge. This paper argues that a key to successful validation of design research lies in the ability to focus on what to validate in advance of how to validate. The paper provide a set of guidelines to support a discussion on how to converge to a claim that actually can be validated. The paper reports on experiences from PhD level course on validation in design research

Synthetic cationic antimicrobial peptides bind with their hydrophobic parts to drug site II of human serum albumin

BACKGROUND: Many biologically active compounds bind to plasma transport proteins, and this binding can be either advantageous or disadvantageous from a drug design perspective. Human serum albumin (HSA) is one of the most important transport proteins in the cardiovascular system due to its great binding capacity and high physiological concentration. HSA has a preference for accommodating neutral lipophilic and acidic drug-like ligands, but is also surprisingly able to bind positively charged peptides. Understanding of how short cationic antimicrobial peptides interact with human serum albumin is of importance for developing such compounds into the clinics. RESULTS: The binding of a selection of short synthetic cationic antimicrobial peptides (CAPs) to human albumin with binding affinities in the μM range is described. Competitive isothermal titration calorimetry (ITC) and NMR WaterLOGSY experiments mapped the binding site of the CAPs to the well-known drug site II within subdomain IIIA of HSA. Thermodynamic and structural analysis revealed that the binding is exclusively driven by interactions with the hydrophobic moieties of the peptides, and is independent of the cationic residues that are vital for antimicrobial activity. Both of the hydrophobic moieties comprising the peptides were detected to interact with drug site II by NMR saturation transfer difference (STD) group epitope mapping (GEM) and INPHARMA experiments. Molecular models of the complexes between the peptides and albumin were constructed using docking experiments, and support the binding hypothesis and confirm the overall binding affinities of the CAPs. CONCLUSIONS: The biophysical and structural characterizations of albumin-peptide complexes reported here provide detailed insight into how albumin can bind short cationic peptides. The hydrophobic elements of the peptides studied here are responsible for the main interaction with HSA. We suggest that albumin binding should be taken into careful consideration in antimicrobial peptide studies, as the systemic distribution can be significantly affected by HSA interactions

Industry Trends to 2040

The engineering design community needs to development tools and methods now to support emerging technological and societal trends. While many forecasts exist for technological and societal changes, this paper reports on the findings of a workshop, which addressed trends in engineering design to 2040. The paper summarises the key findings from the six themes of the workshop: societal trends, ways of working, lifelong learning, technology, modelling and simulation and digitisation; and points to the challenge of understanding how these trends affect each othe

Segmentation-based detection of allelic imbalance and loss-of-heterozygosity in cancer cells using whole genome SNP arrays

A strategy is presented for detection of loss-of-heterozygosity and allelic imbalance in cancer cells from whole genome SNP genotyping data