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INN: Inflated Neural Networks for IPMN Diagnosis

  • Rodney LaLonde
  • Irene Tanner
  • Katerina Nikiforaki
  • Georgios Z. Papadakis
  • Pujan Kandel
  • Candice W. Bolan
  • Michael B. Wallace
  • Ulas BagciEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11768)

Abstract

Intraductal papillary mucinous neoplasm (IPMN) is a precursor to pancreatic ductal adenocarcinoma. While over half of patients are diagnosed with pancreatic cancer at a distant stage, patients who are diagnosed early enjoy a much higher 5-year survival rate of 34% compared to 3% in the former; hence, early diagnosis is key. Unique challenges in the medical imaging domain such as extremely limited annotated data sets and typically large 3D volumetric data have made it difficult for deep learning to secure a strong foothold. In this work, we construct two novel “inflated” deep network architectures, InceptINN and DenseINN, for the task of diagnosing IPMN from multisequence (T1 and T2) MRI. These networks inflate their 2D layers to 3D and bootstrap weights from their 2D counterparts (Inceptionv3 and DenseNet121 respectively) trained on ImageNet to the new 3D kernels. We also extend the inflation process by further expanding the pre-trained kernels to handle any number of input modalities and different fusion strategies. This is one of the first studies to train an end-to-end deep network on multisequence MRI for IPMN diagnosis, and shows that our proposed novel inflated network architectures are able to handle the extremely limited training data (139 MRI scans), while providing an absolute improvement of \(\varvec{8.76}\)% in accuracy for diagnosing IPMN over the current state-of-the-art. Code is publicly available at https://github.com/lalonderodney/INN-Inflated-Neural-Nets.

Keywords

IPMN Pancreatic cancer Inflated networks MRI CAD 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rodney LaLonde
    • 1
  • Irene Tanner
    • 1
  • Katerina Nikiforaki
    • 2
  • Georgios Z. Papadakis
    • 2
  • Pujan Kandel
    • 3
  • Candice W. Bolan
    • 3
  • Michael B. Wallace
    • 3
  • Ulas Bagci
    • 1
    Email author
  1. 1.University of Central Florida (UCF)OrlandoUSA
  2. 2.Foundation for Research and Technology Hellas (FORTH)HeraklionGreece
  3. 3.Mayo ClinicJacksonvilleUSA

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