<div dir="ltr"><span id="gmail-docs-internal-guid-f035bd1b-7fff-5534-f244-80f73688100b" style="color:rgb(0,0,0)"><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Dear all,</span></p><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">We are excited to announce the **<b>Call for Papers</b>** for the upcoming <b>1st Workshop in Data Engineering for Medical Imaging</b> (<a href="https://demi-workshop.github.io">DEMI Workshop</a>), held in conjunction with <b><a href="https://conferences.miccai.org/2023/en/">MICCAI 2023</a>, Vancouver, Canada (October 8-12)</b>. The workshop aims to explore the latest advancements in AI for medical imaging and invites high-quality submissions in the <b>following themes</b> and their intersections. </span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><br></span></p><ol style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:decimal;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b>Data Augmentation and Label Augmentation in the Medical Domain:</b></span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Geometric transformations and application-aware policies for data augmentation</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Data generated from virtual environments, phantoms, or generative models</span></p></li></ul><li dir="ltr" style="list-style-type:decimal;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b>Active Learning and Active Synthesis:</b></span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Methods for finding discriminative and diverse subsets of unlabeled data</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Synthetic data generation for specific clinical applications</span></p></li></ul><li dir="ltr" style="list-style-type:decimal;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b>Federated Learning:</b></span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Distributed data management and learning for addressing privacy concerns and security across institutions or countries</span></p></li></ul><li dir="ltr" style="list-style-type:decimal;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b>Multimodal Learning:</b></span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Approaches to combine data from multiple sources and sensors such as CT, MRI, endoscope, text, audio, depth, etc.</span></p></li></ul><li dir="ltr" style="list-style-type:decimal;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b>Self-Supervised Learning Algorithms for Medical Downstream Tasks:</b></span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Investigation of application-specific relevant pretext tasks for pre-training models in a self-supervised manner</span></p></li></ul><li dir="ltr" style="list-style-type:decimal;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b>Large-Scale Data Management and Data Quality Assessment:</b></span></p></li><ul style="margin-top:0px;margin-bottom:0px"><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Methods for efficient management of large-scale medical data</span></p></li><li dir="ltr" style="list-style-type:disc;font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre"><p dir="ltr" role="presentation" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">Assessment of data quality in medical imaging datasets</span></p></li></ul></ol><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><i>We invite researchers to submit their original contributions to any of these themes. </i></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><br></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">All papers will be peer reviewed and accepted papers will have the opportunity to present their work at the <b>DEMI Workshop at MICCAI 2023</b>, and the papers will be published in the MICCAI Workshop LNCS Springer proceeding. We are pleased to offer awards for high-quality papers.</span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><br></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">The submission deadline is </span><span style="font-size:11pt;font-family:Arial;font-weight:700;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">7th July 2023.</span><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"> </span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><span style="font-size:11pt;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline"><b><br class="gmail-Apple-interchange-newline">For more detailed information on the workshop themes and submission guidelines,</b> please visit our website<b> </b></span><a href="https://demi-workshop.github.io">https://demi-workshop.github.io </a><br></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><br></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">We kindly request you to forward this **<b>Call for Papers**</b> to your mailing list and encourage your colleagues/collaborators and students to contribute to this exciting event. Should you have any questions or require further information, please don't hesitate to reach out to us at </span><span style="font-size:11pt;font-family:Arial;font-weight:700;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><a href="mailto:demi.workshop23@gmail.com">demi.workshop23@gmail.com</a></span><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">.</span></p><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap">We look forward to your submissions and to welcoming you to the DEMI Workshop <a class="gmail_plusreply" id="plusReplyChip-0">@</a> MICCAI 2023!</span></p><br><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b>Best regards,</b></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><i>Sharib Ali</i></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><i>Lecturer, University of Leeds, UK</i></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><i><a href="https://eps.leeds.ac.uk/computing/staff/11465/dr-sharib-ali">https://eps.leeds.ac.uk/computing/staff/11465/dr-sharib-ali</a></i></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><span style="color:rgb(17,85,204);font-family:Arial,Helvetica,sans-serif;font-size:small;white-space:normal;text-decoration:underline"><a href="https://uk.linkedin.com/in/sharib-ali-98388736?trk=profile-badge">https://uk.linkedin.com/in/sharib-ali-98388736?trk=profile-badge</a></span><br></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><br></span></p><p dir="ltr" style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><b><i>On behalf of the DEMI Workshop Organizing Committee</i></b></span></p><p style="line-height:1.38;margin-top:0pt;margin-bottom:0pt"><span style="font-size:11pt;font-family:Arial;font-variant-ligatures:normal;font-variant-alternates:normal;font-variant-numeric:normal;font-variant-east-asian:normal;vertical-align:baseline;white-space:pre-wrap"><i>(Binod Bhattarai, Anita Rau, Anh Nguyen, Ana Namburete, Razvan Caramalau, Danail Stoyanov)</i></span></p></span><br><div dir="ltr" class="gmail_signature" data-smartmail="gmail_signature"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div dir="ltr"><div><br></div></div></div></div></div></div></div></div></div>