| 1. |
- Cervin, Ida, et al.
(författare)
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Improving the creation and reporting of structured findings during digital pathology review
- 2016
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Ingår i: Journal of Pathology Informatics. - : Medknow Publications. - 2229-5089 .- 2153-3539. ; 7:1, s. 32-32
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Tidskriftsartikel (refereegranskat)abstract
- Background: Today, pathology reporting consists of many separate tasks, carried out by multiple people. Common tasks include dictation during case review, transcription, verification of the transcription, report distribution, and report the key findings to follow-up registries. Introduction of digital workstations makes it possible to remove some of these tasks and simplify others. This study describes the work presented at the Nordic Symposium on Digital Pathology 2015, in Linköping, Sweden. Methods: We explored the possibility to have a digital tool that simplifies image review by assisting note-taking, and with minimal extra effort, populates a structured report. Thus, our prototype sees reporting as an activity interleaved with image review rather than a separate final step. We created an interface to collect, sort, and display findings for the most common reporting needs, such as tumor size, grading, and scoring. Results: The interface was designed to reduce the need to retain partial findings in the head or on paper, while at the same time be structured enough to support automatic extraction of key findings for follow-up registry reporting. The final prototype was evaluated with two pathologists, diagnosing complicated partial mastectomy cases. The pathologists experienced that the prototype aided them during the review and that it created a better overall workflow. Conclusions: These results show that it is feasible to simplify the reporting tasks in a way that is not distracting, while at the same time being able to automatically extract the key findings. This simplification is possible due to the realization that the structured format needed for automatic extraction of data can be used to offload the pathologists' working memory during the diagnostic review.
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| 2. |
- Kost, Henning, et al.
(författare)
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Training nuclei detection algorithms with simple annotations
- 2017
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Ingår i: Journal of Pathology Informatics. - : Elsevier BV. - 2229-5089 .- 2153-3539. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Generating good training datasets is essential for machine learning-based nuclei detection methods. However, creating exhaustive nuclei contour annotations, to derive optimal training data from, is often infeasible. Methods: We compared different approaches for training nuclei detection methods solely based on nucleus center markers. Such markers contain less accurate information, especially with regard to nuclear boundaries, but can be produced much easier and in greater quantities. The approaches use different automated sample extraction methods to derive image positions and class labels from nucleus center markers. In addition, the approaches use different automated sample selection methods to improve the detection quality of the classification algorithm and reduce the run time of the training process. We evaluated the approaches based on a previously published generic nuclei detection algorithm and a set of Ki-67-stained breast cancer images. Results: A Voronoi tessellation-based sample extraction method produced the best performing training sets. However, subsampling of the extracted training samples was crucial. Even simple class balancing improved the detection quality considerably. The incorporation of active learning led to a further increase in detection quality. Conclusions: With appropriate sample extraction and selection methods, nuclei detection algorithms trained on the basis of simple center marker annotations can produce comparable quality to algorithms trained on conventionally created training sets.
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| 3. |
- Källén, Hanna, et al.
(författare)
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Towards Grading Gleason Score using Generically Trained Deep convolutional Neural Networks
- 2016
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Ingår i: 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI). - : Institute of Electrical and Electronics Engineers (IEEE). - 9781479923496 - 9781479923502 ; 2016-June, s. 1163-1167
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Konferensbidrag (refereegranskat)abstract
- We developed an automatic algorithm with the purpose to assist pathologists to report Gleason score on malignant prostatic adenocarcinoma specimen. In order to detect and classify the cancerous tissue, a deep convolutional neural network that had been pre-trained on a large set of photographic images was used. A specific aim was to support intuitive interaction with the result, to let pathologists adjust and correct the output. Therefore, we have designed an algorithm that makes a spatial classification of the whole slide into the same growth patterns as pathologists do. The 22-layer network was cut at an earlier layer and the output from that layer was used to train both a random forest classifier and a support vector machines classifier. At a specific layer a small patch of the image was used to calculate a feature vector and an image is represented by a number of those vectors. We have classified both the individual patches and the entire images. The classification results were compared for different scales of the images and feature vectors from two different layers from the network. Testing was made on a dataset consisting of 213 images, all containing a single class, benign tissue or Gleason score 3-5. Using 10-fold cross validation the accuracy per patch was 81 %. For whole images, the accuracy was increased to 89 %.
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| 4. |
- Molin, Jesper, 1987, et al.
(författare)
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A comparative study of input devices for digital slide navigation
- 2015
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Ingår i: Journal of Pathology Informatics. - : Elsevier BV. - 2229-5089 .- 2153-3539. ; 6:7
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Tidskriftsartikel (refereegranskat)abstract
- Quick and seamless integration between input devices and the navigation of digital slides remains a key barrier for many pathologists to "go digital." To better understand this integration, three different input device implementations were compared in terms of time to diagnose, perceived workload and users' preferences. Six pathologists reviewed in total nine cases with a computer mouse, a 6 degrees-of-freedom (6DOF) navigator and a touchpad. The participants perceived significantly less workload (P
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| 5. |
- Molin, Jesper, 1987
(författare)
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Designing a digital pathology workstation for routine practice
- 2015
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The role of the pathology lab is important in the future of cancer care. In orderto further personalize the care for cancer patients, more precise review of tumorspecimens is needed in order to guide clinicians between different treatmentstrategies.New digital imaging technologies is one promising possibility that might allowpathologists performing more and better work with the same amount ofresources. Early scanning systems and workstations have been shown to beinefficient and have not met the pathologists’ needs, who still perform most oftheir diagnostic work with mechanical microscopes.In this thesis, we analyze the pathologist's work with early digital workstationsand present a set of new solutions in order to increase the performance of theinteraction with these systems.First, we review the implementation process of two current digital systems intwo pathology labs in Sweden (Paper I), followed by study of the navigationbehavior that is performed by pathologists when they explore large digital slidesof cancer specimens (Paper II).With a specific focus on design solutions that work within medical routinepractice, three different input devices for navigation in large images wascompared with pathologists as participants (Paper III), as well as a visualizationtechnique, inspired by semantic zoom in order to facilitate certain tasks forpathologists (Paper IV).The results provided in this thesis points towards the same conclusion that havemade in other domains: When good usability engineering is combined withtechnological advances, this can make novel technology become useful for real.For a Human-Computer Interaction (HCI) researcher, the pathologist caserepresents an especially demanding use of zoomable user interfaces. This hasdriven us to enhance efficiency of such interfaces further in order for them tobecome useful. The research findings offered within this thesis are particularlyimportant to the field of digital pathology. However, our findings could alsohave a bearing on the design of zoomable user interfaces.
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| 6. |
- Molin, Jesper, 1987
(författare)
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Diagnostic Review with Digital Pathology: Design of digitals tools for routine diagnostic use
- 2016
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Digital pathology is a novel technology currently being implemented world wide. Thisthesis summarizes four years of HCI and visualization research and provides an overallunderstanding of designing workstation software for pathologists. A human-centereddesign approach has been used to create a number of design interventions.The thesis covers three main areas of inquiry: Understanding pathologists’ problemsolving processes during diagnostic review, how to build different digital tools to supportthose processes, and how to incorporate digital image analysis algorithms when buildingthese tools.The thesis consist of a kappa that provides background and context, to the remainingappended papers. The papers describe studies covering, pathologists’ navigationstrategies in gigapixel sized images, the usability of different input devices and structuredreporting interfaces, how principles from volume rendering can be used for multi-scaleimages, and how make to use of machine learning algorithms to support pathologists’diagnostic processes.Together, these design projects show how digital pathology images can be usedto create tools to make pathologists more productive. This will make it possible forpathology laboratories to replace their diagonstic workflow using glass slides, with aworkflow based on digital images.
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| 7. |
- Molin, Jesper, 1987, et al.
(författare)
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Feature-enhancing zoom to facilitate Ki-67 hot spot detection
- 2014
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Ingår i: Progress in Biomedical Optics and Imaging - Proceedings of SPIE. - : SPIE. - 1605-7422. - 9780819498342 ; 9041
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Konferensbidrag (refereegranskat)abstract
- Image processing algorithms in pathology commonly include automated decision points such as classifications. While this enables efficient automation, there is also a risk that errors are induced. A different paradigm is to use image processing for enhancements without introducing explicit classifications. Such enhancements can help pathologists to increase efficiency without sacrificing accuracy. In our work, this paradigm has been applied to Ki-67 hot spot detection. Ki-67 scoring is a routine analysis to quantify the proliferation rate of tumor cells. Cell counting in the hot spot, the region of highest concentration of positive tumor cells, is a method increasingly used in clinical routine. An obstacle for this method is that while hot spot selection is a task suitable for low magnification, high magnification is needed to discern positive nuclei, thus the pathologist must perform many zooming operations. We propose to address this issue by an image processing method that increases the visibility of the positive nuclei at low magnification levels. This tool displays the modified version at low magnification, while gradually blending into the original image at high magnification. The tool was evaluated in a feasibility study with four pathologists targeting routine clinical use. In a task to compare hot spot concentrations, the average accuracy was 75±4.1% using the tool and 69±4.6% without it (n=4). Feedback on the system, gathered from an observer study, indicate that the pathologists found the tool useful and fitting in their existing diagnostic process. The pathologists judged the tool to be feasible for implementation in clinical routine.
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| 8. |
- Molin, Jesper, 1987, et al.
(författare)
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Scale Stain: Multi-Resolution Feature Enhancement in Pathology Visualization
- 2016
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- Digital whole-slide images of pathological tissue samples have recently become feasible for use within routine diagnostic practice. These gigapixel sized images enable pathologists to perform reviews using computer workstations instead of microscopes. Existing workstations visualize scanned images by providing a zoomable image space that reproduces the capabilities of the microscope. This paper presents a novel visualization approach that enables filtering of the scale-space according to color preference. The visualization method reveals diagnostically important patterns that are otherwise not visible. The paper demonstrates how thisapproach has been implemented into a fully functional prototype that lets the user navigate the visualization parameter space in real time. The prototype was evaluated for two common clinical tasks with eight pathologists in a within-subjects study. The data reveal thattask efficiency increased by 15% using the prototype, with maintained accuracy. By analyzing behavioral strategies, it was possible to conclude that efficiency gain was caused by a reduction of the panning needed to perform systematic search of the images. The prototype system was well received by the pathologists who did not detect any risks that would hinder use in clinical routine.
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| 9. |
- Molin, Jesper, 1987, et al.
(författare)
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Slide navigation patterns among pathologists with long experience of digital review
- 2015
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Ingår i: Histopathology. - : Wiley. - 0309-0167 .- 1365-2559. ; 67:2, s. 185-192
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Tidskriftsartikel (refereegranskat)abstract
- Aims: In order to develop efficient digital pathologyworkstations, we studied the navigation patterns ofpathologists diagnosing whole-slide images. To gain abetter understanding of these patterns, we built aconceptual model based on observations. We alsodetermined whether or not new navigation patternshave emerged among pathologists with extensive digitalexperience.Methods and results: Five pathologists were asked todiagnose a set of four cases while thinking out loud.The navigation within the digital slides was recordedand divided into re-occurring navigation actions. Thepathologists reused the same type of actions, but theiroccurrence differed. The most common action was aslow panning that followed an edge structure orcovered an area systematically, which accounted for30.2% of all actions and had a median duration of7.2 s. Of all the actions, 49% were carried out withinthe navigation overview and 38% of the actionscould not have been performed with a conventionalmicroscope.Conclusions: The new navigation possibilities in thedigital workstation were used to a large extent. Thedivision of actions into different concepts can be usedto find and prioritize between existing user interfacedesigns as well as to understand the different navigationstyles used by different pathologists.
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| 10. |
- Molin, Jesper, 1987, et al.
(författare)
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Understanding Design for Automated Image Analysis in Digital Pathology
- 2016
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Ingår i: 9th Nordic Conference on Human-Computer Interaction, NordiCHI 2016, Gothenburg, Sweden, 23-27 October 2016. - New York, NY, USA : ACM. - 9781450347631 ; 23-27-October-2016:58
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Konferensbidrag (refereegranskat)abstract
- Digital pathology is an emerging healthcare field taking advantage of technology that allows digitization of microscopy images. Such digitization enables the use of automated digital image analysis techniques, which could be beneficial for the diagnostic review and prognosis of a variety of conditions. As yet, human-computer interaction (HCI) issues in this field, which is mostly based on visual analysis, have not been systematically explored. Based on reflecting on the process of designing and deploying systems for digital pathology, we propose a new understanding to design automated tools for such environments. We used meeting minutes, design briefs, interviews, personal notes and other artifacts to conduct a thematic analysis. This enabled us to establish four design considerations for introducing digital image analysis to routine pathology that concern level of detail, verification, communication and transparency.
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