Faculty Profiles - KAMIYA Tohru

Papers - KAMIYA Tohru

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3次元点群の位置合わせによる顔の対称面検出

細木　大祐, 陸, 金, 木村, 大河内, 野添, 中村

第38回日本医用画像工学会大会予稿集 599 - 605 2019.07

3D-CNN for Automatic Detection of Lung Nodules from Temporal Subtraction Images Reviewed

YOSHINO Yuriko, LU Huimin, KIM Hyoungseop, MURAKAMI Seiichi, AOKI Takatoshi, KIDO Shoji

Medical Imaging and Information Sciences ( MEDICAL IMAGING AND INFORMATION SCIENCES ) 36 ( 2 ) 77 - 82 2019.06

Authorship：Corresponding author Language：Japanese Publishing type：Research paper (scientific journal)

<p>A temporal subtraction image is obtained by subtracting a previous image, which are warped to match between the structures of the previous image and one of a current image, from the current image. The temporal subtraction technique removes normal structures and enhances interval changes such as new lesions and changes of existing abnormalities from a medical image. However, many artifacts remain on a temporal subtraction image and these can be detected as false positives on the subtraction images. In this paper, we propose a 3D-CNN after initial nodule candidates are detected using temporal subtraction technique. To compare the proposed 3D-CNN, we used 7 model architectures, which are 3D ShallowNet, 3D-AlexNet, 3D-VGG11, 3D-VGG13, 3D-ResNet8, 3D-ResNet20, 3D-ResNet32, with these performance on 28 thoracic MDCT cases including 28 small-sized lung nodules. The higher performance is showed on 3D-AlexNet.</p>

DOI： 10.11318/mii.36.77

CiNii Article

CiNii Research

Other Link： https://search.jamas.or.jp/link/ui/2019298826

3D convolutional neural networks for automatic detection of lung nodules from temporal subtraction images Reviewed

International Journal of Computer Assited Radiology and Surgery S71 - S72 2019.06

Reduction of false-positive polyp detections in CT colonography using multiscale 3D residual networks Reviewed

S67 - S68 2019.06

3D registration method based on intensity gradient information for temporal subtraction technique in thoracic MDCT image Reviewed

nternational Journal of Computer Assited Radiology and Surgery S22 - S23 2019.06

CONet: A Cognitive Ocean Network Reviewed International journal

Lu H., Wang D., Li Y., Li J., Li X., Kim H., Serikawa S., Humar I.

IEEE Wireless Communications 26 ( 3 ) 90 - 96 2019.06

畳み込みニューラルネットワークを用いた指骨CR画像からの骨粗しょう症の識別 Reviewed

畠野、村上、植村、陸、金、青木

医用画像情報学会雑誌 ( 医用画像情報学会雑誌 ) 36 ( 2 ) 72 - 76 2019.06

３D-CNNによる経時的差分像上の結節状陰影検出 Reviewed

芳野、陸、金、村上、青木、木戸

医用画像情報学会雑誌 36 ( 2 ) 77 - 82 2019.06

The Cognitive Internet of Vehicles for Autonomous Driving Reviewed International journal

Lu H., Liu Q., Tian D., Li Y., Kim H., Serikawa S.

IEEE Network 33 ( 3 ) 65 - 73 2019.05

Low-light underwater image enhancement for deep-sea tripod Reviewed International journal

Yujie Li, Jianru Li, Yun Li, H KIM, S SERIKAWA

IEEE Access 7 44080 - 44086 2019.04

Ensemble 3D residual network(E3D-ResNet) for reduction of false-positive polyp detections in CTcolonography Reviewed

1095013-1 - 1095013-7 2019.03

対称性解析に基づく３次元データから顔の対称面の検出

細木、陸、金、木村、大河内、野添、中村

信学技報、IE2018-158 285 - 286 2019.03

対称性解析に基づく口唇裂３次元点群からの正中面抽出法

山田、陸、金、木村、大河内、野添、中村

信学技報、IE2018-158 287 - 290 2019.03

経時的差分像上の関心領域内の統計的特徴量に基づく結節状陰影の自動検出

金，田中，陸，村上，青木，木戸

電子情報通信学会総合大会 108 - 108 2019.03

YOROを用いた海中生物のロバスト自律追跡

陸、金

動的画像処理実用化ワークショップ 65 - 66 2019.03

Clinical Applications of Multidisciplunary Computational Anatomy to Diagnosis

202 - 212 2019.03

Recognition of surrounding environment from electric wheelchair videos based on modified YOLOv2 Reviewed International journal

Sakai Y., Lu H., Tan J.K., Kim H.

Future Generation Computer Systems 92 157 - 161 2019.03

CNNを用いた指骨CR画像からの骨粗しょう症の自動識別 Reviewed

畠野、村上、植村、陸、金、青木

Medical Imaging Technology 37 ( 2 ) 107 - 115 2019.03

Dust removal from high turbid underwater images using convolutional neural networks Reviewed International journal

Li Y., Zhang Y., Xu X., He L., Serikawa S., Kim H.

Optics and Laser Technology 110 2 - 6 2019.02

Statistical shape model building method using surface registration and model prototype Reviewed International journal

Li G., Wu J., Xiao Z., Kim H.S., Ogunbona P.O.

Optics and Laser Technology 110 234 - 238 2019.02

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