BreastScreening: On the Use of Multi-Modality in Medical Imaging Diagnosis

This paper describes the field research, design and comparative deployment of a multimodal medical imaging user interface for breast screening. The main contributions described here are threefold: 1) The design of an advanced visual interface for multimodal diagnosis of breast cancer (BreastScreening); 2) Insights from the field comparison of Single-Modality vs Multi-Modality screening of breast cancer diagnosis with 31 clinicians and 566 images; and 3) The visualization of the two main types of breast lesions in the following image modalities: (i) MammoGraphy (MG) in both Craniocaudal (CC) and Mediolateral oblique (MLO) views; (ii) UltraSound (US); and (iii) Magnetic Resonance Imaging (MRI). We summarize our work with recommendations from the radiologists for guiding the future design of medical imaging interfaces.

[1]  Gustavo Carneiro,et al.  One Shot Segmentation: Unifying Rigid Detection and Non-Rigid Segmentation Using Elastic Regularization , 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[2]  Katharina Scheiter,et al.  Overlooking: the nature of gaze behavior and anomaly detection in expert dentists , 2018, MCPMD@ICMI.

[3]  Morten Fjeld,et al.  Notes from the front lines: lessons learnt from designing for improving medical imaging data sharing , 2014, NordiCHI.

[4]  Kwan-Hoong Ng,et al.  Technical Specifications of Medical Imaging Equipment , 2017 .

[5]  Johan H. C. Reiber,et al.  The effect of stereoscopy and motion cues on 3D interpretation task performance , 2010, AVI.

[6]  Ann Blandford,et al.  Understanding People: A Course on Qualitative and Quantitative HCI Research Methods , 2017, CHI Extended Abstracts.

[7]  Lin Yang,et al.  Translating and Segmenting Multimodal Medical Volumes with Cycle- and Shape-Consistency Generative Adversarial Network , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[8]  Laurent Grisoni,et al.  Touchless interaction with medical images based on 3D hand cursors supported by single-foot input: A case study in dentistry , 2019, Journal of Biomedical Informatics.

[9]  Ian D. Reid,et al.  Deep Reinforcement Learning for Detecting Breast Lesions from DCE-MRI , 2019, Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics.

[10]  Erik Ziegler,et al.  LesionTracker: Extensible Open-Source Zero-Footprint Web Viewer for Cancer Imaging Research and Clinical Trials. , 2017, Cancer research.

[11]  Desney S. Tan,et al.  Designing patient-centric information displays for hospitals , 2010, CHI.

[12]  Harini Veeraraghavan,et al.  Appearance Constrained Semi-Automatic Segmentation from DCE-MRI is Reproducible and Feasible for Breast Cancer Radiomics: A Feasibility Study , 2018, Scientific Reports.

[13]  Luís Rosado,et al.  A novel framework for supervised mobile assessment and risk triage of skin lesions , 2015, 2015 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth).

[14]  Jorge S. Marques,et al.  Fast segmentation of the left ventricle in cardiac MRI using dynamic programming , 2018, Comput. Methods Programs Biomed..

[15]  Carl Gutwin,et al.  Anchoring Effects and Troublesome Asymmetric Transfer in Subjective Ratings , 2019, CHI.

[16]  Jorge S. Marques,et al.  Fast and accurate segmentation of the LV in MR volumes using a deformable model with dynamic programming , 2017, 2017 IEEE International Conference on Image Processing (ICIP).

[17]  Marco Porta.  Browsing large collections of images through unconventional visualization techniques , 2006, AVI '06.

[18]  Karon E. MacLean,et al.  Crafting diversity in radiology image stack scrolling: control and annotations , 2014, Conference on Designing Interactive Systems.

[19]  Bin Zheng,et al.  Association between background parenchymal enhancement of breast MRI and BIRADS rating change in the subsequent screening , 2018, Medical Imaging.

[20]  C. Borrás.  Defining the Medical Imaging Requirements for a Rural Health Center , 2017 .

[21]  Jacinto C. Nascimento,et al.  Segmenting The Left Ventricle In Cardiac In Cardiac MRI: From Handcrafted To Deep Region Based Descriptors , 2019, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

[22]  Sébastien Jodogne,et al.  The Orthanc Ecosystem for Medical Imaging , 2018, Journal of Digital Imaging.

[23]  Paolo Buono,et al.  Building a qualified annotation dataset for skin lesion analysis trough gamification , 2018, AVI.

[24]  Lauren Wilcox,et al.  "Hello AI": Uncovering the Onboarding Needs of Medical Practitioners for Human-AI Collaborative Decision-Making , 2019, Proc. ACM Hum. Comput. Interact..

[25]  J. J. Higgins,et al.  The aligned rank transform for nonparametric factorial analyses using only anova procedures , 2011, CHI.

[26]  Laurel D. Riek,et al.  Designing collaborative healthcare technology for the acute care workflow , 2015, 2015 9th International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth).

[27]  Gustavo Carneiro,et al.  Training Medical Image Analysis Systems like Radiologists , 2018, MICCAI.

[28]  Jacinto C. Nascimento,et al.  Towards Touch-Based Medical Image Diagnosis Annotation , 2017, ISS.

[29]  E. Henriksen,et al.  The efficacy of using computer-aided detection (CAD) for detection of breast cancer in mammography screening: a systematic review , 2019, Acta radiologica.

[30]  Giuseppe De Pietro,et al.  Toward a natural interface to virtual medical imaging environments , 2008, AVI '08.

[31]  Daniel Mendes,et al.  VRRRRoom: Virtual Reality for Radiologists in the Reading Room , 2017, CHI.

[32]  Mari Tyllinen,et al.  We Need Numbers!: Heuristic Evaluation during Demonstrations (HED) for Measuring Usability in IT System Procurement , 2016, CHI.

[33]  Panayiotis Koutsabasis,et al.  Mid-Air Browsing and Selection in Image Collections , 2016, AVI.

[34]  Takeo Igarashi,et al.  Interactive Volume Segmentation with Threshold Field Painting , 2016, UIST.

[35]  M. Dryden,et al.  BI-RADS® fifth edition: A summary of changes. , 2017, Diagnostic and interventional imaging.

[36]  Preethi Srinivas,et al.  Modeling Clinical Workflow in Daily ICU Rounds to Support Task-based Patient Monitoring and Care , 2015, CSCW Companion.