Efficient Anomaly Detection with Generative Adversarial Network for Breast Ultrasound Imaging

Fujioka, Tomoyuki; Kubota, Kazunori; Mori, M.; Kikuchi, Yuka; Katsuta, Leona; Kimura, Mizuki; Yamaga, Emi; Adachi, Mio; Oda, Goshi; Nakagawa, Tsuyoshi; Kitazume, Yoshio; Tateishi, Ukihide

doi:10.3390/diagnostics10070456

Cited by 30 publications

(22 citation statements)

References 28 publications

(31 reference statements)

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“…COVID-19, coronavirus disease 2019; CT, computed tomography; RT-PCR, reverse transcription-polymerase chain reaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2. suspected of having COVID-19 pneumonia, it is crucial to make a comprehensive assessment based on both CT images and clinical findings. In recent years, artificial intelligence, especially deep learning, has been greatly developed and applied to medical imaging [16][17][18][19]. Ni et al utilized a deep learning model for automatic detection of abnormalities in chest CT images of COVID-19 patients.…”

Section: Discussionmentioning

confidence: 99%

“…In the city of Wuhan, Hubei province, China, a highly contagious disease was first identified at the end of 2019, which was later proven to be caused by a novel coronavirus (2019-nCoV or severe acute respiratory syndrome coronavirus 2) [1]. As of 10 August 2020, more than 19,718,000 people worldwide have been infected with coronavirus disease 2019 (COVID- 19), and more than 728,000 have died [2].…”

Section: Introductionmentioning

confidence: 99%

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Evaluation of the Usefulness of CO-RADS for Chest CT in Patients Suspected of Having COVID-19

et al. 2020

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The purpose of this study was to use the Coronavirus Disease 2019 (COVID-19) Reporting and Data System (CO-RADS) to evaluate the chest computed tomography (CT) images of patients suspected of having COVID-19, and to investigate its diagnostic performance and interobserver agreement. The Dutch Radiological Society developed CO-RADS as a diagnostic indicator for assessing suspicion of lung involvement of COVID-19 on a scale of 1 (very low) to 5 (very high). We investigated retrospectively 154 adult patients with clinically suspected COVID-19, between April and June 2020, who underwent chest CT and reverse transcription-polymerase chain reaction (RT-PCR). The patients’ average age was 61.3 years (range, 21–93), 101 were male, and 76 were RT-PCR positive. Using CO-RADS, four radiologists evaluated the chest CT images. Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated. Interobserver agreement was calculated using the intraclass correlation coefficient (ICC) by comparing the individual reader’s score to the median of the remaining three radiologists. The average sensitivity was 87.8% (range, 80.2–93.4%), specificity was 66.4% (range, 51.3–84.5%), and AUC was 0.859 (range, 0.847–0.881); there was no significant difference between the readers (p > 0.200). In 325 (52.8%) of 616 observations, there was absolute agreement among observers. The average ICC of readers was 0.840 (range, 0.800–0.874; p < 0.001). CO-RADS is a categorical taxonomic evaluation scheme for COVID-19 pneumonia, using chest CT images, that provides outstanding performance and from substantial to almost perfect interobserver agreement for predicting COVID-19.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of the Usefulness of CO-RADS for Chest CT in Patients Suspected of Having COVID-19

et al. 2020

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“…Recent advances in computing have helped leverage the artificial intelligence (AI) technology for image classification; several studies have applied AI for evaluation of breast US imaging for diagnostic purposes [ 13 , 14 , 15 , 16 ]. Future prospects for use of AI for evaluation of US findings of axillary lymph nodes appear promising.…”

Section: Discussionmentioning

confidence: 99%

Clinical Usefulness of Ultrasound-Guided Fine Needle Aspiration and Core Needle Biopsy for Patients with Axillary Lymphadenopathy

et al. 2021

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Background and Objectives: It is necessary to properly diagnose and manage axillary lymphadenopathy caused by a variety of diseases. This study aimed to evaluate the utility of ultrasound (US)-guided sampling in patients with axillary lymphadenopathy. Materials and Methods: Patients with axillary lymphadenopathy (excluding patients with newly diagnosed breast cancer) who underwent US-guided fine needle aspiration (FNA) or core needle biopsy (CNB) at a single center between February 2016 and September 2020 were retrospectively examined. The association between US imaging findings and malignancy was investigated and the diagnostic performance of US-guided sampling was assessed. Results: Fifty-five patients (including eight males) were included in the study; of these, 34 patients (61.8%) were finally diagnosed with a malignant lymph node lesion. Twenty-two patients (40.0%) had undergone FNA and 33 (60.0%) had undergone CNB. Larger short and long axis diameters, thicker lymph node cortex, and the absence of fatty hilum on the US were significantly associated with malignancy (p < 0.05). The diagnostic performance of FNA, CNB, and FNA + CNB was excellent (sensitivity, specificity, and accuracy of 0.909, 0.900, and 0.917 for FNA, 0.958, 1.000, and 0.970 for CNB, and 0.941, 0.952, and 0.945 for FNA + CNB, respectively). Conclusions: US-guided FNA and CNB play an important role in the diagnosis and management of patients with axillary lymphadenopathy

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“…One of the most interesting breakthroughs in this area is the invention of generative adversarial networks (GANs). [27][28][29] GANs are a special type of neural network, one focusing on image generation and the other on discrimination. GAN has been reported to have broad applicability in medical imaging for image synthesis.…”

Section: Synthetic Mri In the Breastmentioning

confidence: 99%

Investigating the Image Quality and Utility of Synthetic MRI in the Breast

et al. 2021

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Purpose: Synthetic MRI reconstructs multiple sequences in a single acquisition. In the present study, we aimed to compare the image quality and utility of synthetic MRI with that of conventional MRI in the breast. Methods:We retrospectively collected the imaging data of 37 women (mean age: 55.1 years; range: 20-78 years) who had undergone both synthetic and conventional MRI of T2-weighted, T1-weighted, and fatsuppressed (FS)-T2-weighted images. Two independent breast radiologists evaluated the overall image quality, anatomical sharpness, contrast between tissues, image homogeneity, and presence of artifacts of synthetic and conventional MRI on a 5-point scale (5 = very good to 1 = very poor). The interobserver agreement between the radiologists was evaluated using weighted kappa.Results: For synthetic MRI, the acquisition time was 3 min 28 s. On the 5-point scale evaluation of overall image quality, although the scores of synthetic FS-T2-weighted images (4.01 ± 0.56) were lower than that of conventional images (4.95 ± 0.23; P < 0.001), the scores of synthetic T1-and T2-weighted images (4.95 ± 0.23 and 4.97 ± 0.16) were comparable with those of conventional images (4.92 ± 0.27 and 4.97 ± 0.16; P = 0.484 and 1.000, respectively). The kappa coefficient of conventional MRI was fair (0.53; P < 0.001), and that of conventional MRI was fair (0.46; P < 0.001). Conclusion:The image quality of synthetic T1-and T2-weighted images was similar to that of conventional images and diagnostically acceptable, whereas the quality of synthetic T2-weighted FS images was inferior to conventional images. Although synthetic MRI images of the breast have the potential to provide efficient image diagnosis, further validation and improvement are required for clinical application.

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Efficient Anomaly Detection with Generative Adversarial Network for Breast Ultrasound Imaging

Cited by 30 publications

References 28 publications

Evaluation of the Usefulness of CO-RADS for Chest CT in Patients Suspected of Having COVID-19

Evaluation of the Usefulness of CO-RADS for Chest CT in Patients Suspected of Having COVID-19

Clinical Usefulness of Ultrasound-Guided Fine Needle Aspiration and Core Needle Biopsy for Patients with Axillary Lymphadenopathy

Investigating the Image Quality and Utility of Synthetic MRI in the Breast

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