581 research outputs found
R1_supplementary_FEP_striatalFC – Supplemental material for Resting-state functional connectivity of the striatum predicts improvement in negative symptoms and general functioning in patients with first-episode psychosis: A 1-year naturalistic follow-up study
No full textSupplemental material, R1_supplementary_FEP_striatalFC for Resting-state functional connectivity of the striatum predicts improvement in negative symptoms and general functioning in patients with first-episode psychosis: A 1-year naturalistic follow-up study by Sanghoon Oh, Minah Kim, Taekwan Kim, Tae Young Lee and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
A performance comparison of convolutional neural network‐based image denoising methods: The effect of loss functions on low‐dose CT images
No full textPURPOSE: Convolutional neural network (CNN)‐based image denoising techniques have shown promising results in low‐dose CT denoising. However, CNN often introduces blurring in denoised images when trained with a widely used pixel‐level loss function. Perceptual loss and adversarial loss have been proposed recently to further improve the image denoising performance. In this paper, we investigate the effect of different loss functions on image denoising performance using task‐based image quality assessment methods for various signals and dose levels. METHODS: We used a modified version of U‐net that was effective at reducing the correlated noise in CT images. The loss functions used for comparison were two pixel‐level losses (i.e., the mean‐squared error and the mean absolute error), Visual Geometry Group network‐based perceptual loss (VGG loss), adversarial loss used to train the Wasserstein generative adversarial network with gradient penalty (WGAN‐GP), and their weighted summation. Each image denoising method was applied to reconstructed images and sinogram images independently and validated using the extended cardiac‐torso (XCAT) simulation and Mayo Clinic datasets. In the XCAT simulation, we generated fan‐beam CT datasets with four different dose levels (25%, 50%, 75%, and 100% of a normal‐dose level) using 10 XCAT phantoms and inserted signals in a test set. The signals had two different shapes (spherical and spiculated), sizes (4 and 12 mm), and contrast levels (60 and 160 HU). To evaluate signal detectability, we used a detection task SNR (tSNR) calculated from a non‐prewhitening model observer with an eye filter. We also measured the noise power spectrum (NPS) and modulation transfer function (MTF) to compare the noise and signal transfer properties. RESULTS: Compared to CNNs without VGG loss, VGG‐loss‐based CNNs achieved a more similar tSNR to that of the normal‐dose CT for all signals at different dose levels except for a small signal at the 25% dose level. For a low‐contrast signal at 25% or 50% dose, adding other losses to the VGG loss showed more improved performance than only using VGG loss. The NPS shapes from VGG‐loss‐based CNN closely matched that of normal‐dose CT images while CNN without VGG loss overly reduced the mid‐high‐frequency noise power at all dose levels. MTF also showed VGG‐loss‐based CNN with better‐preserved high resolution for all dose and contrast levels. It is also observed that additional WGAN‐GP loss helps improve the noise and signal transfer properties of VGG‐loss‐based CNN. CONCLUSIONS: The evaluation results using tSNR, NPS, and MTF indicate that VGG‐loss‐based CNNs are more effective than those without VGG loss for natural denoising of low‐dose images and WGAN‐GP loss improves the denoising performance of VGG‐loss‐based CNNs, which corresponds with the qualitative evaluation
A convolutional neural network‐based model observer for breast CT images
No full textPurpose In this paper, we propose a convolutional neural network (CNN)-based efficient model observer for breast computed tomography (CT) images. Methods We first showed that the CNN-based model observer provided similar detection performance to the ideal observer (IO) for signal-known-exactly and background-known-exactly detection tasks with an uncorrelated Gaussian background noise image. We then demonstrated that a single-layer CNN without a nonlinear activation function provided similar detection performance in breast CT images to the Hotelling observer (HO). To train the CNN-based model observer, we generated simulated breast CT images to produce a training dataset in which different background noise structures were generated using filtered back projection with a ramp, or a Hanning weighted ramp, filter. Circular, elliptical, and spiculated signals were used for the detection tasks. The optimal depth and the number of channels for the CNN-based model observer were determined for each task. The detection performances of the HO and a channelized Hotelling observer (CHO) with Laguerre-Gauss (LG) and partial least squares (PLS) channels were also estimated for comparison. Results The results showed that the CNN-based model observer provided higher detection performance than the HO, LG-CHO, and PLS-CHO for all tasks. In addition, it was shown that the proposed CNN-based model observer provided higher detection performance than the HO using a smaller training dataset. Conclusions In the presence of nonlinearity in the CNN, the proposed CNN-based model observer showed better performance than other linear observers.
supplementary_materials – Supplemental material for Adjunctive use of anti-inflammatory drugs for schizophrenia: A meta-analytic investigation of randomized controlled trials
No full textSupplemental material, supplementary_materials for Adjunctive use of anti-inflammatory drugs for schizophrenia: A meta-analytic investigation of randomized controlled trials by Myeongju Cho, Tae Young Lee, Yoo Bin Kwak, Youngwoo Brian Yoon, Minah Kim and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
revised_supp_tableS4_corr – Supplemental material for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes
No full textSupplemental material, revised_supp_tableS4_corr for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes by Yoo Bin Kwak, Minah Kim, Kang Ik Kevin Cho, Junhee Lee, Tae Yong Lee and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
revised_Supplementary_legend – Supplemental material for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes
No full textSupplemental material, revised_Supplementary_legend for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes by Yoo Bin Kwak, Minah Kim, Kang Ik Kevin Cho, Junhee Lee, Tae Yong Lee and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
revised_supp_figS3 – Supplemental material for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes
No full textSupplemental material, revised_supp_figS3 for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes by Yoo Bin Kwak, Minah Kim, Kang Ik Kevin Cho, Junhee Lee, Tae Yong Lee and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
revised_supp_figS2 – Supplemental material for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes
No full textSupplemental material, revised_supp_figS2 for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes by Yoo Bin Kwak, Minah Kim, Kang Ik Kevin Cho, Junhee Lee, Tae Yong Lee and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
Supplementary – Supplemental material for Disturbed thalamocortical connectivity in unaffected relatives of schizophrenia patients with a high genetic loading
No full textSupplemental material, Supplementary for Disturbed thalamocortical connectivity in unaffected relatives of schizophrenia patients with a high genetic loading by Kang Ik K Cho, Minah Kim, Youngwoo Bryan Yoon, Junhee Lee, Tae Young Lee and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
revised_supp_tableS1_comorbidity – Supplemental material for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes
No full textSupplemental material, revised_supp_tableS1_comorbidity for Reduced cortical thickness in subjects at clinical high risk for psychosis and clinical attributes by Yoo Bin Kwak, Minah Kim, Kang Ik Kevin Cho, Junhee Lee, Tae Yong Lee and Jun Soo Kwon in Australian & New Zealand Journal of Psychiatry</p
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