Medical Imaging: Computer-Aided Diagnosis

Keyphrases

Publications

2019

Mohammad Mahdi Shiraz Bhurwani, Alexander R. Podgorsak, Anusha Ramesh Chandra, Ryan A. Rava, Kenneth V. Snyder, Elad I. Levy, Jason M. Davies, Adnan H. Siddiqui, Ciprian N. Ionita
Feasibility study of deep neural networks to classify intracranial aneurysms using angiographic parametric imaging. Medical Imaging: Computer-Aided Diagnosis (2019)
Manuel Berger, Martin Pillei, Andreas H. Mehrle, Wolfgang Recheis, Florian Kral, Michael Kraxner, Wolfgang Freysinger
Predicting resection volumes within the nasal cavity to improve patients breathing. Medical Imaging: Computer-Aided Diagnosis (2019)
Thom Scheeve, Maarten R. Struyvenberg, Wouter L. Curvers, Albert J. de Groof, Erik J. Schoon, Jacques J. G. H. M. Bergman, Fons van der Sommen, Peter H. N. de With
A novel clinical gland feature for detection of early Barrett's neoplasia using volumetric laser endomicroscopy. Medical Imaging: Computer-Aided Diagnosis (2019)
Lin Li, Rakesh Shiradkar, Ahmad Algohary, Patrick Leo, Cristina Magi-Galluzzi, Eric Klein, Andrei Purysko, Anant Madabhushi
Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk score. Medical Imaging: Computer-Aided Diagnosis (2019)
Tomoki Uemura, Janne J. Näppi, Huimin Lu, Hyoungseop Kim, Rie Tachibana, Toru Hironaka, Hiroyuki Yoshida
Ensemble 3D residual network (E3D-ResNet) for reduction of false-positive polyp detections in CT colonography. Medical Imaging: Computer-Aided Diagnosis (2019)
Joanna Jaworek-Korjakowska
Acral melanocytic lesion segmentation with a convolution neural network (U-Net). Medical Imaging: Computer-Aided Diagnosis (2019)
Hayato Itoh, Holger R. Roth, Yuichi Mori, Masashi Misawa, Masahiro Oda, Shin-ei Kudo, Kensaku Mori
Polyp-size classification with RGB-D features for colonoscopy. Medical Imaging: Computer-Aided Diagnosis (2019)
Kayla R. Mendel, Hui Li, Nabihah Tayob, Randa El-Zein, Isabelle Bedrosian, Maryellen L. Giger
Temporal mammographic registration for evaluation of architecture changes in cancer risk assessment. Medical Imaging: Computer-Aided Diagnosis (2019)
Mariana P. Bento, Roberto Souza, Marina Salluzzi, Richard Frayne
Reliability of computer-aided diagnosis tools with multi-center MR datasets: impact of training protocol. Medical Imaging: Computer-Aided Diagnosis (2019)
Eric Wu, Lubomir M. Hadjiiski, Ravi K. Samala, Heang-Ping Chan, Kenny H. Cha, Caleb Richter, Richard H. Cohan, Elaine M. Caoili, Chintana Paramagul, Ajjai Alva, Alon Z. Weizer
Deep learning based bladder cancer treatment response assessment. Medical Imaging: Computer-Aided Diagnosis (2019)
Guillaume Vanoost, Yashin Dicente Cid, Daniel L. Rubin, Adrien Depeursinge
A lung graph model for the classification of interstitial lung diseases on CT images. Medical Imaging: Computer-Aided Diagnosis (2019)
Jintao Ren, Arash Moaddel H., Ellen M. Hauge, Kresten K. Keller, Rasmus K. Jensen, François Lauze
Automatic detection and localization of bone erosion in hand HR-pQCT. Medical Imaging: Computer-Aided Diagnosis (2019)
Xiangyuan Ma, Caleb Fisher, Jun Wei, Mark A. Helvie, Heang-Ping Chan, Chuan Zhou, Lubomir M. Hadjiiski, Yao Lu
Multi-path deep learning model for automated mammographic density categorization. Medical Imaging: Computer-Aided Diagnosis (2019)
Yi Wang, Marc J. Pomeroy, Weiguo Cao, Yongfeng Gao, Edward Sun, Samuel Stanley III, Juan Carlos Bucobo, Zhengrong Liang
Differentiation of polyps by clinical colonoscopy via integrated color information, image derivatives and machine learning. Medical Imaging: Computer-Aided Diagnosis (2019)
Qiyuan Hu, Heather M. Whitney, Alexandra Edwards, John Papaioannou, Maryellen L. Giger
Radiomics and deep learning of diffusion-weighted MRI in the diagnosis of breast cancer. Medical Imaging: Computer-Aided Diagnosis (2019)
Faisal Mahmood, Jeremiah W. Johnson, Ziyun Yang, Nicholas J. Durr
Fusing attributes predicted via conditional GANs for improved skin lesion classification (Conference Presentation). Medical Imaging: Computer-Aided Diagnosis (2019)
Bo Wang, Yang Lei, Jiwoong Jason Jeong, Tonghe Wang, Yingzi Liu, Sibo Tian, Pretesh Patel, Xiaojun Jiang, Ashesh B. Jani, Hui Mao, Walter J. Curran, Tian Liu, Xiaofeng Yang
Automatic MRI prostate segmentation using 3D deeply supervised FCN with concatenated atrous convolution. Medical Imaging: Computer-Aided Diagnosis (2019)
Ruchika Verma, Ramon Correa, Virginia Hill, Niha G. Beig, Abdelkader Mahammedi, Anant Madabhushi, Pallavi Tiwari
Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in Glioblastoma. Medical Imaging: Computer-Aided Diagnosis (2019)
Thom Scheeve, Ramon-Michel Schreuder, Fons van der Sommen, Joep E. G. IJspeert, Evelien Dekker, Erik J. Schoon, Peter H. N. de With
Computer-aided classification of colorectal polyps using blue-light and linked-color imaging. Medical Imaging: Computer-Aided Diagnosis (2019)
Jordan D. Fuhrman, Jennie Crosby, Rowena Yip, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger
Detection and classification of coronary artery calcifications in low dose thoracic CT using deep learning. Medical Imaging: Computer-Aided Diagnosis (2019)
Jianfei Liu, Haewon Jung, Tao Liu, Johnny Tam
Longitudinal matching of in vivo adaptive optics images of fluorescent cells in the human eye using stochastically consistent superpixels. Medical Imaging: Computer-Aided Diagnosis (2019)
Matias Benitez, James Tian, Mark Kelly, Vignesh Selvakumaran, Matthew Phelan, Maciej A. Mazurowski, Joseph Y. Lo, Geoffrey D. Rubin, Ricardo Henao
Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reports. Medical Imaging: Computer-Aided Diagnosis (2019)
Yuxing Tang, Youbao Tang, Mei Han, Jing Xiao, Ronald M. Summers
Deep adversarial one-class learning for normal and abnormal chest radiograph classification. Medical Imaging: Computer-Aided Diagnosis (2019)
Ge Cui, Jiwoong Jason Jeong, Yang Lei, Tonghe Wang, Tian Liu, Walter J. Curran, Hui Mao, Xiaofeng Yang
Machine-learning-based classification of Glioblastoma using MRI-based radiomic features. Medical Imaging: Computer-Aided Diagnosis (2019)
Karen Drukker, Iman El-Bawab, Alexandra Edwards, Christopher Doyle, John Papaioannou, Kirti Kulkarni, Maryellen L. Giger
Breast MRI radiomics for the pre-treatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients. Medical Imaging: Computer-Aided Diagnosis (2019)
Shuaitong Zhang, Yafei Qi, Jingwei Wei, Jianxing Niu, Dongsheng Gu, Yuqi Han, Xiaohan Hao, Yali Zang, Jie Tian
Radiomics analysis potentially reduces over-diagnosis of prostate cancer with PSA levels of 4-10 ng/ml based on DWI data. Medical Imaging: Computer-Aided Diagnosis (2019)
Ravi K. Samala, Heang-Ping Chan, Caleb Richter, Lubomir M. Hadjiiski, Chuan Zhou, Jun Wei
Analysis of deep convolutional features for detection of lung nodules in computed tomography. Medical Imaging: Computer-Aided Diagnosis (2019)
Faisal Mahmood, Ziyun Yang, Richard J. Chen, Daniel Borders, Wenhao Xu, Nicholas J. Durr
Polyp segmentation and classification using predicted depth from monocular endoscopy. Medical Imaging: Computer-Aided Diagnosis (2019)
Jianhuo Shen, Teng Li, Chuanrui Hu, Hong He, Jianfei Liu
Automatic cell segmentation using mini-u-net on fluorescence in situ hybridization images. Medical Imaging: Computer-Aided Diagnosis (2019)
Kenny H. Cha, Nicholas Petrick, Aria Pezeshk, Christian G. Graff, Diksha Sharma, Andreu Badal, Aldo Badano, Berkman Sahiner
Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic images. Medical Imaging: Computer-Aided Diagnosis (2019)
Rui Hou, Yinhao Ren, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, Eun-Sil Shelley Hwang, Joseph Y. Lo
Malignant microcalcification clusters detection using unsupervised deep autoencoders. Medical Imaging: Computer-Aided Diagnosis (2019)
Ruixiang Tang, Fakrul Islam Tushar, Songyue Han, Rui Hou, Geoffrey D. Rubin, Joseph Y. Lo
Classification of chest CT using case-level weak supervision. Medical Imaging: Computer-Aided Diagnosis (2019)
Hainan Sang, Jiang Meng, Yang Liu, Zhengrong Liang, Hongbing Lu
The detection of non-polypoid colorectal lesions using the texture feature extracted from intact colon wall: a pilot study. Medical Imaging: Computer-Aided Diagnosis (2019)
Devanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle
Computer-aided detection using non-convolutional neural network Gaussian processes. Medical Imaging: Computer-Aided Diagnosis (2019)
Adora M. DSouza, Anas Z. Abidin, Axel Wismüller
Automated identification of thoracic pathology from chest radiographs with enhanced training pipeline. Medical Imaging: Computer-Aided Diagnosis (2019)
Yoon-Chul Kim, Ji-Eun Lee, Inwu Yu, In-Young Baek, Han-Gil Jeong, Beom-Joon Kim, Joon-Kyung Seong, Jong-Won Chung, Oh Young Bang, Woo-Keun Seo
Evaluation of U-net segmentation models for infarct volume measurement in acute ischemic stroke: comparison with fixed ADC threshold-based methods. Medical Imaging: Computer-Aided Diagnosis (2019)
Dhanuj Gandikota, Lubomir M. Hadjiiski, Heang-Ping Chan, Kenny H. Cha, Ravi Samala, Elaine M. Caoili, Richard H. Cohan, Alon Z. Weizer, Ajjai Alva, Chintana Paramagul, Jun Wei, Chuan Zhou
Bladder cancer staging in CT urography: estimation and validation of decision thresholds for a radiomics-based decision support system. Medical Imaging: Computer-Aided Diagnosis (2019)
Bas H. M. van der Velden, Bob D. de Vos, Claudette E. Loo, Hugo J. Kuijf, Ivana Isgum, Kenneth G. A. Gilhuijs
Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing. Medical Imaging: Computer-Aided Diagnosis (2019)
P. P. J. H. Langenhuizen, H. van Gorp, Sveta Zinger, J. Verheul, S. Leenstra, Peter H. N. de With
Dose distribution as outcome predictor for Gamma Knife radiosurgery on vestibular schwannoma. Medical Imaging: Computer-Aided Diagnosis (2019)
Noriyuki Takahashi, Yuki Shinohara, Toshibumi Kinoshita, Tomomi Ohmura, Keisuke Matsubara, Yongbum Lee, Hideto Toyoshima
Computerized identification of early ischemic changes in acute stroke in noncontrast CT using deep learning. Medical Imaging: Computer-Aided Diagnosis (2019)
Sang Ho Lee, Peijin Han, Russell K. Hales, K. Ranh Voong, Todd R. McNutt, Junghoon Lee
Identifying optimal input using multilevel radiomics and nested cross-validation for predicting pulmonary function in lung cancer patients treated with radiotherapy. Medical Imaging: Computer-Aided Diagnosis (2019)
Young-Wouk Kim, Sebastián Roberto Tarando, Pierre-Yves Brillet, Catalin I. Fetita
Image biomarkers for quantitative analysis of idiopathic interstitial pneumonia. Medical Imaging: Computer-Aided Diagnosis (2019)
Fatemeh Zabihollahy, Eranga Ukwatta
Fully-automated segmentation of optic disk from retinal images using deep learning techniques. Medical Imaging: Computer-Aided Diagnosis (2019)
Theo Cleland, James G. Mainprize, Olivier Alonzo-Proulx, Jennifer A. Harvey, Roberta A. Jong, Anne L. Martel, Martin J. Yaffe
Use of convolutional neural networks to predict risk of masking by mammographic density. Medical Imaging: Computer-Aided Diagnosis (2019)
Zhe Guo, Ning Guo, Kuang Gong, Quanzheng Li
Automatic multi-modality segmentation of gross tumor volume for head and neck cancer radiotherapy using 3D U-Net. Medical Imaging: Computer-Aided Diagnosis (2019)
Lei Zhang, Ruimei Chai, Aly A. Mohamed, Bingjie Zheng, Zhimeng Luo, Shandong Wu
Automated deep-learning method for whole-breast segmentation in diffusion-weighted breast MRI. Medical Imaging: Computer-Aided Diagnosis (2019)
Faranak Aghaei, Alan B. Hollingsworth, Seyedehnafiseh Mirniaharikandehei, Yunzhi Wang, Hong Liu, Bin Zheng
Developing a new quantitative imaging marker to predict pathological complete response to neoadjuvant chemotherapy. Medical Imaging: Computer-Aided Diagnosis (2019)
Seyedehnafiseh Mirniaharikandehei, Morteza Heidari, Gopichandh Danala, Wei Qian, Yuchen Qiu, Bin Zheng
Association of computer-aided detection results and breast cancer risk. Medical Imaging: Computer-Aided Diagnosis (2019)
Shou Wang, Xi Chen, Zhenyu Liu, Qingxia Wu, Yongbei Zhu, Meiyun Wang, Jie Tian
Radiomics analysis on T2-MR image to predict lymphovascular space invasion in cervical cancer. Medical Imaging: Computer-Aided Diagnosis (2019)

volume 10950, 2019

Medical Imaging 2019: Computer-Aided Diagnosis, San Diego, California, United States, 16-21 February 2019 Medical Imaging: Computer-Aided Diagnosis 10950 (2019)