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Multi-task Lung Nodule Detection in Chest Radiographs with a Dual Head Network

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 (MICCAI 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13431))

Abstract

Lung nodules can be an alarming precursor to potential lung cancer. Missed nodule detections during chest radiograph analysis remains a common challenge among thoracic radiologists. In this work, we present a multi-task lung nodule detection algorithm for chest radiograph analysis. Unlike past approaches, our algorithm predicts a global-level label indicating nodule presence along with local-level labels predicting nodule locations using a Dual Head Network (DHN). We demonstrate the favorable nodule detection performance that our multi-task formulation yields in comparison to conventional methods. In addition, we introduce a novel Dual Head Augmentation (DHA) strategy tailored for DHN, and we demonstrate its significance in further enhancing global and local nodule predictions.

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Notes

  1. 1.

    The complete list of transformations are detailed in the supplementary materials.

  2. 2.

    FROC and AFROC are computed with an Intersection over Union (IOU) threshold of 0.4, and the FROC-AUC is computed with a False Positive Per-Image up to 1.

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Acknowledgements

We would like to thank Che-Han Chang and the anonymous reviewers for their valuable suggestions. We also thank the members: Chun-Nan Chou, Fu-Chieh Chang, Yu-Quan Zhang, and Hao-Jen Wang for their support in collecting annotated data, and Yi-Hsiang Chin for his efforts in conducting experiments.

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Authors and Affiliations

  1. HTC DeepQ, Taipei, Taiwan

    Chen-Han Tsai & Yu-Shao Peng

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  1. Chen-Han Tsai
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  2. Yu-Shao Peng
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Corresponding author

Correspondence to Chen-Han Tsai .

Editor information

Editors and Affiliations

  1. Rochester Institute of Technology, Rochester, NY, USA

    Linwei Wang

  2. Chinese University of Hong Kong, Hong Kong, Hong Kong

    Qi Dou

  3. University of Virginia, Charlottesville, VA, USA

    P. Thomas Fletcher

  4. National Center for Tumor Diseases (NCT/UCC), Dresden, Germany

    Stefanie Speidel

  5. Case Western Reserve University, Cleveland, OH, USA

    Shuo Li

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Tsai, CH., Peng, YS. (2022). Multi-task Lung Nodule Detection in Chest Radiographs with a Dual Head Network. In: Wang, L., Dou, Q., Fletcher, P.T., Speidel, S., Li, S. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2022. MICCAI 2022. Lecture Notes in Computer Science, vol 13431. Springer, Cham. https://doi.org/10.1007/978-3-031-16431-6_67

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  • DOI: https://doi.org/10.1007/978-3-031-16431-6_67

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