Table of Contents

• Use of a convolutional neural network for aneurysm identification in digital subtraction angiographyAlexander R. Podgorsak, Mohammad Mahdi Bhurwani, Ryan A. Rava, Anusha Ramesh Chandra, Ciprian N. Ionita. [doi]
• Stability of radiomic features of liver lesions from manual delineation in CT scansJan Hendrik Moltz. [doi]
• Artifact-driven sampling schemes for robust female pelvis CBCT segmentation using deep learningAnnika Hänsch, Volker Dicken, Jan Klein 0001, Tomasz Morgas, Benjamin Haas, Horst K. Hahn. [doi]
• Bladder cancer staging in CT urography: estimation and validation of decision thresholds for a radiomics-based decision support systemDhanuj 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 0002, Chuan Zhou. [doi]
• Effect of diversity of patient population and acquisition systems on the use of radiomics and machine learning for classification of 2, 397 breast lesionsHeather M. Whitney, Yu Ji, Hui Li, Alexandra Edwards, John Papaioannou, Peifang Liu, Maryellen L. Giger. [doi]
• Deep learning of sub-regional breast parenchyma in mammograms for localized breast cancer risk predictionGiacomo Nebbia, Aly A. Mohamed, Ruimei Chai, Bingjie Zheng, Margarita L. Zuley, Shandong Wu. [doi]
• Fully automated segmentation of left ventricular myocardium from 3D late gadolinium enhancement magnetic resonance images using a U-net convolutional neural network-based modelFatemeh Zabihollahy, James A. White, Eranga Ukwatta. [doi]
• Augmenting LIDC dataset using 3D generative adversarial networks to improve lung nodule detectionChufan Gao, Stephen Clark, Jacob D. Furst, Daniela Raicu. [doi]
• Development and validation of a radiomics-based method for macrovascular invasion prediction in hepatocellular carcinoma with prognostic implicationJingwei Wei, Sirui Fu, Shauitong Zhang, Jie Zhang, Dongsheng Gu, Xiaoqun Li, Xudong Chen, Xiaofeng He, Jianfeng Yan, Ligong Lu, Jie Tian. [doi]
• Identifying optimal input using multilevel radiomics and nested cross-validation for predicting pulmonary function in lung cancer patients treated with radiotherapySang Ho Lee, Peijin Han, Russell K. Hales, K. Ranh Voong, Todd R. McNutt, Junghoon Lee. [doi]
• Improved interpretability for computer-aided severity assessment of retinopathy of prematurityMara Graziani, James M. Brown, Vincent Andrearczyk, Veysi Yildiz, J. Peter Campbell, Deniz Erdogmus, Stratis Ioannidis, Michael F. Chiang, Jayashree Kalpathy-Cramer, Henning Müller. [doi]
• Automated identification of thoracic pathology from chest radiographs with enhanced training pipelineAdora M. DSouza, Anas Z. Abidin, Axel Wismüller. [doi]
• Weakly-supervised deep learning of interstitial lung disease types on CT imagesChenglong Wang, Takayasu Moriya, Yuichiro Hayashi, Holger Roth, Le Lu, Masahiro Oda, Hirotugu Ohkubo, Kensaku Mori. [doi]
• Quantitative vessel tortuosity radiomics on baseline non-contrast lung CT predict response to immunotherapy and are prognostic of overall survivalMehdi Alilou, Pranjal Vaidya, Mohammadhadi Khorrami, Alexia Zagouras, Pradnya Patil, Kaustav Bera, Pingfu Fu, Vamsidhar Velcheti, Anant Madabhushi. [doi]
• A deep learning method for volumetric breast density estimation from processed full field digital mammogramsDoiriel Vanegas C., Mahlet A. Birhanu, Nico Karssemeijer, Albert Gubern-Mérida, Michiel Kallenberg. [doi]
• Radiomic features derived from pre-operative multi-parametric MRI of prostate cancer are associated with Decipher risk scoreLin Li, Rakesh Shiradkar, Ahmad Algohary, Patrick Leo, Cristina Magi-Galluzzi, Eric Klein, Andrei Purysko, Anant Madabhushi. [doi]
• Modeling normal brain asymmetry in MR images applied to anomaly detection without segmentation and data annotationSamuel Botter Martins, Barbara Caroline Benato, Bruna Ferreira Silva, Clarissa Lyn Yasuda, Alexandre Xavier Falcão. [doi]
• Radiomics analysis potentially reduces over-diagnosis of prostate cancer with PSA levels of 4-10 ng/ml based on DWI dataShuaitong Zhang, Yafei Qi, Jingwei Wei, Jianxing Niu, Dongsheng Gu, Yuqi Han, Xiaohan Hao, Yali Zang, Jie Tian. [doi]
• Exploring features towards semantic characterization of lung nodules in computed tomography imagesMaysa M. G. Macedo, Dário A. B. Oliveira. [doi]
• Evaluation of U-net segmentation models for infarct volume measurement in acute ischemic stroke: comparison with fixed ADC threshold-based methodsYoon-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. [doi]
• Lung tissue characterization for emphysema differential diagnosis using deep convolutional neural networksMohammadreza Negahdar, David Beymer. [doi]
• Classifying abnormalities in computed tomography radiology reports with rule-based and natural language processing modelsSongyue Han, James Tian, Mark Kelly, Vignesh Selvakumaran, Ricardo Henao, Geoffrey D. Rubin, Joseph Y. Lo. [doi]
• Exploratory learning with convolutional autoencoder for discrimination of architectural distortion in digital mammographyHelder Cesar Rodigues de Oliveira, Carlos F. E. Melo, Juliana H. Catani, Nestor de Barros, Marcelo Andrade da Costa Vieira. [doi]
• Multi-path deep learning model for automated mammographic density categorizationXiangyuan Ma, Caleb Fisher, Jun Wei 0002, Mark A. Helvie, Heang-Ping Chan, Chuan Zhou, Lubomir M. Hadjiiski, Yao Lu. [doi]
• An ensemble of U-Net architecture variants for left atrial segmentationC. Wang, Martin Rajchl, A. D. C. Chan, Eranga Ukwatta. [doi]
• Differentiation of polyps by clinical colonoscopy via integrated color information, image derivatives and machine learningYi Wang, Marc Pomeroy, Weiguo Cao, Yongfeng Gao, Edward Sun, Samuel Stanley III, Juan Carlos Bucobo, Zhengrong Liang. [doi]
• Early detection of retinopathy of prematurity stage using deep learning approachSupriti Mulay, Keerthi Ram, Mohanasankar Sivaprakasam, Anand Vinekar. [doi]
• A lung graph model for the classification of interstitial lung diseases on CT imagesGuillaume Vanoost, Yashin Dicente Cid, Daniel L. Rubin, Adrien Depeursinge. [doi]
• Breast density follow-up decision support system using deep convolutional modelsSun Young Park, Dustin Sargent, David Richmond. [doi]
• Visual evidence for interpreting diagnostic decision of deep neural network in computer-aided diagnosisSeong-Tae Kim, Jae-Hyeok Lee, Yong Man Ro. [doi]
• Dose distribution as outcome predictor for Gamma Knife radiosurgery on vestibular schwannomaP. P. J. H. Langenhuizen, H. van Gorp, Sveta Zinger, J. Verheul, S. Leenstra, Peter H. N. de With. [doi]
• The detection of non-polypoid colorectal lesions using the texture feature extracted from intact colon wall: a pilot studyHainan Sang, Jiang Meng, Yang Liu 0093, Zhengrong Liang, Hongbing Lu. [doi]
• PHT-bot: a deep learning based system for automatic risk stratification of COPD patients based upon signs of pulmonary hypertensionDavid Chettrit, Orna Bregman-Amitai, Itamar Tamir, Amir Bar, Eldad Elnekave. [doi]
• Reproducibility of CT-based texture feature quantification of simulated and 3D-printed trabecular bone: influence of noise and reconstruction kernelNada Kamona, Qin Li, Benjamin P. Berman, Berkman Sahiner, Nicholas Petrick. [doi]
• Artificial intelligence for point of care radiograph quality assessmentSatyananda Kashyap, Mehdi Moradi, Alexandros Karargyris, Joy T. Wu, Michael Morris, Babak Saboury, Eliot L. Siegel, Tanveer F. Syeda-Mahmood. [doi]
• Associations between mammographic phenotypes and histopathologic features in ductal carcinoma in situRuvini Navaratna, Aimilia Gastounioti, Meng Kang Hsieh, Lauren Pantalone, Marie Shelanski, Emily F. Conant, Despina Kontos. [doi]
• Efficient learning in computer-aided diagnosis through label propagationSamuel Berglin, Eura Shin, Jacob D. Furst, Daniela Raicu. [doi]
• Association of computer-aided detection results and breast cancer riskSeyedehnafiseh Mirniaharikandehei, Morteza Heidari, Gopichandh Danala, Wei Qian, Yuchen Qiu, Bin Zheng 0001. [doi]
• A shell and kernel descriptor based joint deep learning model for predicting breast lesion malignancyZhiguo Zhou, Genggeng Qin, Pingkun Yan, Hongxia Hao, Steve Jiang, Jing Wang. [doi]
• Machine learning for segmenting cells in corneal endothelium imagesChaitanya Kolluru, Beth A. Benetz, Naomi Joseph, Harry J. Menegay, Jonathan H. Lass, David Wilson. [doi]
• Efficient detection of vascular structures using locally connected filteringAmélé Florence Kouvahe, Catalin I. Fetita. [doi]
• Automatic anatomy partitioning of the torso region on CT images by using a deep convolutional network with majority votingXiangrong Zhou, Takuya Kojima, Song Wang, Xinxin Zhou, Takeshi Hara, Taiki Nozaki, Masaki Matsusako, Hiroshi Fujita 0001. [doi]
• A novel clinical gland feature for detection of early Barrett's neoplasia using volumetric laser endomicroscopyThom 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. [doi]
• Patient-specific outcome simulation after surgical correction of Pectus Excavatum: a preliminary studyMafalda Couto, João Gomes Fonseca, António H. J. Moreira, Tiago Henriques-Coelho, Jaime C. Fonseca, António C. M. Pinho, Jorge Correia-Pinto, João L. Vilaça. [doi]
• A combination of intra- and peritumoral features on baseline CT scans is associated with overall survival in non-small cell lung cancer patients treated with immune checkpoint inhibitors: a multi-agent multi-site studyMohammadhadi Khorrami, Mehdi Alilou, Prateek Prasanna, Pradnya Patil, Pirya Velu, Kaustav Bera, Pingfu Fu, Vamsidhar Velcheti, Anant Madabhushi. [doi]
• 3D fully convolutional network-based segmentation of lung nodules in CT images with a clinically inspired data synthesis methodAtsushi Yaguchi, Kota Aoyagi, Akiyuki Tanizawa, Yoshiharu Ohno. [doi]
• Automatic MR kidney segmentation for autosomal dominant polycystic kidney diseaseGuangrui Mu, Yiyi Ma, Miaofei Han, Yiqiang Zhan, Xiang Zhou, Yaozong Gao. [doi]
• Automated measurement of fetal right-myocardial performance index from pulsed wave Doppler spectrumRahul Suresh, Srinivasan Sivanandan, Nitin Singhal, JinYong Lee, Mi-Young Lee, Hye-Sung Won. [doi]
• Computer-aided CT image features improving the malignant risk prediction in pulmonary nodules suspicious for lung cancerYoshiki Kawata, Noboru Niki, Masahiko Kusumoto, Hironobu Ohmatsu, K. Aokage, G. Ishii, Y. Matsumoto, Takaaki Tsuchida, Kenji Eguchi, M. Kaneko. [doi]
• Acral melanocytic lesion segmentation with a convolution neural network (U-Net)Joanna Jaworek-Korjakowska. [doi]
• Non-invasive genotype prediction of chromosome 1p/19q co-deletion by development and validation of an MRI-based radiomics signature in lower-grade gliomasYuqi Han, Zhen Xie, Yali Zang, Shuaitong Zhang, Dongsheng Gu, Jingwei Wei, Chao Li, Hongyan Chen, Jiang Du, Di Dong, Jie Tian, Dabiao Zhou. [doi]
• Lung segmentation based on a deep learning approach for dynamic chest radiographyYuki Kitahara, Rie Tanaka, Holger R. Roth, Hirohisa Oda, Kensaku Mori, Kazuo Kasahara, Isao Matsumoto. [doi]
• Using multi-task learning to improve diagnostic performance of convolutional neural networksMengjie Fang, Di Dong, Ruijia Sun, Li Fan, Yingshi Sun, Shiyuan Liu, Jie Tian. [doi]
• Radiomics and deep learning of diffusion-weighted MRI in the diagnosis of breast cancerQiyuan Hu, Heather M. Whitney, Alexandra Edwards, John Papaioannou, Maryellen L. Giger. [doi]
• U-Net based automatic carotid plaque segmentation from 3D ultrasound imagesRan Zhou, Wei Ma, Aaron Fenster, Mingyue Ding. [doi]
• Improving pulmonary lobe segmentation on expiratory CTs by using aligned inspiratory CTsOliver Weinheimer, Mark Oliver Wielpütz, Philip Konietzke, Claus Peter Heussel, Hans-Ulrich Kauczor, Terry E. Robinson, Craig J. Galbán. [doi]
• The U-net and its impact to medical imaging (Conference Presentation)Bernardino Romera-Paredes. [doi]
• Automatic strategy for extraction of anthropometric measurements for the diagnostic and evaluation of deformational plagiocephaly from infant's head modelsBruno Oliveira 0002, Helena R. Torres, Fernando Veloso, Estela Vilhena, Nuno F. Rodrigues, Jaime C. Fonseca, Pedro Morais, João L. Vilaça. [doi]
• Age prediction using a large chest x-ray datasetAlexandros Karargyris, S. Kashyap, J. T. Wu, A. Sharma, M. Moradi, Tanveer Fathima Syeda-Mahmood. [doi]
• Deep learning convolutional neural networks for the estimation of liver fibrosis severity from ultrasound textureAlex Treacher, Daniel Beauchamp, Bilal Quadri, David Fetzer, Abhinav Vij, Takeshi Yokoo, Albert Montillo. [doi]
• Visualizing and explaining deep learning predictions for pneumonia detection in pediatric chest radiographsSivaramakrishnan Rajaraman, Sema Candemir, George R. Thoma, Sameer K. Antani. [doi]
• Malignant microcalcification clusters detection using unsupervised deep autoencodersRui Hou, Yinhao Ren, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, E. Shelley Hwang, Joseph Y. Lo. [doi]
• Polyp classification by Weber's Law as texture descriptor for clinical colonoscopyYi Wang, Marc Pomeroy, Weiguo Cao, Yongfeng Gao, Edward Sun, Samuel Stanley III, Zhengrong Liang, Juan Carlos Bucobo. [doi]
• Breast parenchyma analysis and classification for breast masses detection using texture feature descriptors and neural networks in dedicated breast CT imagesMarco Caballo, Jonas Teuwen, Ritse Mann, Ioannis Sechopoulos. [doi]
• Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRISukanya Iyer, Marwa Ismail, Benita Tamrazi, Ashley Margol, Ruchika Verma, Ramon Correa, Prateek Prasanna, Niha Beig, Kaustav Bera, Volodymyr Statsevych, Alexander R. Judkins, Anant Madabhushi, Pallavi Tiwari. [doi]
• Computer-aided detection and classification of microcalcification clusters on full field digital mammograms using deep convolution neural networkGuanxiong Cai, Yanhui Guo, Weiguo Chen, Hui Zeng, Yuanpin Zhou, Yao Lu. [doi]
• Computerized identification of early ischemic changes in acute stroke in noncontrast CT using deep learningNoriyuki Takahashi, Yuki Shinohara, Toshibumi Kinoshita, Tomomi Ohmura, Keisuke Matsubara, Yongbum Lee, Hideto Toyoshima. [doi]
• A deep learning approach to classify atherosclerosis using intracoronary optical coherence tomographyLambros S. Athanasiou, Max L. Olender, José M. de la Torre Hernandez, Eyal Ben-Assa, Elazer R. Edelman. [doi]
• Automatic MRI prostate segmentation using 3D deeply supervised FCN with concatenated atrous convolutionBo 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. [doi]
• 2.5D CNN model for detecting lung disease using weak supervisionYue Geng, Yinhao Ren, Rui Hou, Songyue Han, Geoffrey D. Rubin, Joseph Y. Lo. [doi]
• Automatic cell segmentation using mini-u-net on fluorescence in situ hybridization imagesJianhuo Shen, Teng Li, Chuanrui Hu, Hong He, Jianfei Liu. [doi]
• Pre-trained deep convolutional neural networks for the segmentation of malignant pleural mesothelioma tumor on CT scansEyjolfur Gudmundsson, Christopher M. Straus, Samuel G. Armato. [doi]
• CT-realistic data augmentation using generative adversarial network for robust lymph node segmentationYoubao Tang, Sooyoun Oh, YuXing Tang, Jing Xiao, Ronald M. Summers. [doi]
• Deep learning for automated screening and semantic segmentation of age-related and juvenile atrophic macular degenerationZiyuan Wang, SriniVas R. Sadda, Zhihong Hu. [doi]
• Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growingBas H. M. van der Velden, Bob D. de Vos, Claudette E. Loo, Hugo J. Kuijf, Ivana Isgum, Kenneth G. A. Gilhuijs. [doi]
• Radiogenomic characterization of response to chemo-radiation therapy in glioblastoma is associated with PI3K/AKT/mTOR and apoptosis signaling pathwaysNiha Beig, Prateek Prasanna, Virginia Hill, Ruchika Verma, Vinay Varadan, Anant Madabhushi, Pallavi Tiwari. [doi]
• Combining deep learning methods and human knowledge to identify abnormalities in computed tomography (CT) reportsMatias Benitez, James Tian, Mark Kelly, Vignesh Selvakumaran, Matthew Phelan, Maciej A. Mazurowski, Joseph Y. Lo, Geoffrey D. Rubin, Ricardo Henao. [doi]
• A probabilistic approach for interpretable deep learning in liver cancer diagnosisClinton J. Wang, Charlie A. Hamm, Brian S. Letzen, James S. Duncan. [doi]
• Automated deep-learning method for whole-breast segmentation in diffusion-weighted breast MRILei Zhang, Ruimei Chai, Aly A. Mohamed, Bingjie Zheng, Zhimeng Luo, Shandong Wu. [doi]
• Computationally-efficient wavelet-based characterization of breast tumors using conventional B-mode ultrasound imagesManar N. Mahmoud, Muhammad A. Rushdi, Iman Ewais, Eman Hosny, Hanan Gewefel, Ahmed M. Mahmoud. [doi]
• Use of convolutional neural networks to predict risk of masking by mammographic densityTheo Cleland, James G. Mainprize, Olivier Alonzo-Proulx, Jennifer A. Harvey, Roberta A. Jong, Anne L. Martel, Martin J. Yaffe. [doi]
• Breast dispersion imaging using undersampled rapid dynamic contrast-enhanced MRILinxi Shi, Subashini Srinivasan, Brian A. Hargreaves, Bruce L. Daniel. [doi]
• Towards deep radiomics: nodule malignancy prediction using CNNs on feature imagesRahul Paul, Dmitry Cherezov, Matthew B. Schabath, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof. [doi]
• Transfer learning for automatic cancer tissue detection using multispectral photoacoustic imagingKamal Jnawali, Bhargava Chinni, Vikram Dogra, Navalgund Rao. [doi]
• Predicting unnecessary nodule biopsy for a small lung cancer screening dataset by less-abstractive deep featuresFangfang Han, Linkai Yan, Chen Li, Shouliang Qi, William Moore, Zhengrong Liang, Wei Qian. [doi]
• Learning-based automatic segmentation on arteriovenous malformations from contract-enhanced CT imagesTonghe Wang, Yang Lei, Ghazal Shafai-Erfani, Xiaojun Jiang, Xue-dong, Jun Zhou, Tian Liu, Walter J. Curran, Xiaofeng Yang, Hui-Kuo Shu. [doi]
• Multiview mammographic mass detection based on a single shot detection systemYinhao Ren, Rui Hou, Dehan Kong, Yue Geng, Lars J. Grimm, Jeffrey R. Marks, Joseph Y. Lo. [doi]
• Computer-aided detection using non-convolutional neural network Gaussian processesDevanshu Agrawal, Hong-Jun Yoon, Georgia D. Tourassi, Jacob D. Hinkle. [doi]
• Breast MRI radiomics for the pre-treatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patientsKaren Drukker, Iman El-Bawab, Alexandra Edwards, Christopher Doyle, John Papaioannou, Kirti Kulkarni, Maryellen L. Giger. [doi]
• Developing a new quantitative imaging marker to predict pathological complete response to neoadjuvant chemotherapyFaranak Aghaei, Alan B. Hollingsworth, Seyedehnafiseh Mirniaharikandehei, Yunzhi Wang, Hong Liu, Bin Zheng. [doi]
• Deep learning based bladder cancer treatment response assessmentEric 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. [doi]
• Texture-based prostate cancer classification on MRI: how does inter-class size mismatch affect measured system performance?R. Alfano, D. Soetemans, Glenn S. Bauman, Mena Gaed, Madeleine Moussa, J. A. Gomez, Joseph L. Chin, Stephen E. Pautler, Aaron D. Ward. [doi]
• Feasibility study of deep neural networks to classify intracranial aneurysms using angiographic parametric imagingMohammad 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. [doi]
• Fine-grained lung nodule segmentation with pyramid deconvolutional neural networkXinzhuo Zhao, Wenqing Sun, Wei Qian, Shouliang Qi, Jianjun Sun, Bo Zhang, Zhigang Yang. [doi]
• Fusing attributes predicted via conditional GANs for improved skin lesion classification (Conference Presentation)Faisal Mahmood, Jeremiah Johnson, Ziyun Yang, Nicholas J. Durr. [doi]
• Improved polyp classification by inclusion of the surrounding colon wall texturesMarc Pomeroy, Almas Abbasi, Kevin Baker, Matthew A. Barish, Samuel Stanley, Kenneth Ng, Perry J. Pickhardt, Zhengrong Liang. [doi]
• Variability in radiomics features among iDose reconstruction levelsJoseph J. Foy, Mena Shenouda, Sahar Ramahi, Samuel G. Armato, Daniel Ginat. [doi]
• Identifying disease-free chest x-ray images with deep transfer learningKen C. L. Wong, Mehdi Moradi, Joy T. Wu, Tanveer F. Syeda-Mahmood. [doi]
• Radiomics of the lesion habitat on pre-treatment MRI predicts response to chemo-radiation therapy in GlioblastomaRuchika Verma, Ramon Correa, Virginia Hill, Niha Beig, Abdelkader Mahammedi, Anant Madabhushi, Pallavi Tiwari. [doi]
• Lung nodule retrieval using semantic similarity estimatesMark Loyman, Hayit Greenspan. [doi]
• Similar CT image retrieval method based on lesion nature and their three-dimensional distributionYasutaka Moriwaki, Nobuhiro Miyazaki, Hiroaki Takebe, Takayuki Baba, Hiroaki Terada, Toru Higaki, Kazuo Awai, Machiko Nakagawa, Akio Ozawa, Kennji Kitayama, Yasuharu Ogino. [doi]
• A semi-supervised CNN learning method with pseudo-class labels for vascular calcification detection on low dose CT scansJiamin Liu, Jianhua Yao, Mohammadhadi Bagheri, Ronald M. Summers. [doi]
• 2D and 3D bladder segmentation using U-Net-based deep-learningXiangyuan Ma, Lubomir M. Hadjiiski, Jun Wei 0002, Heang-Ping Chan, Kenny H. Cha, Richard H. Cohan, Elaine M. Caoili, Ravi Samala, Chuan Zhou, Yao Lu. [doi]
• Synthesis and texture manipulation of screening mammograms using conditional generative adversarial networkDehan Kong, Yinhao Ren, Rui Hou, Lars J. Grimm, Jeffrey R. Marks, Joseph Y. Lo. [doi]
• Diagnosis of OCD using functional connectome and Riemann kernel PCAXiaodan Xing, Lili Jin, Feng Shi, Ziwen Peng. [doi]
• Analysis of deep convolutional features for detection of lung nodules in computed tomographyRavi K. Samala, Heang-Ping Chan, Caleb Richter, Lubomir M. Hadjiiski, Chuan Zhou, Jun Wei 0002. [doi]
• DCE-MRI based analysis of intratumor heterogeneity by decomposing method for prediction of HER2 status in breast cancerPeng Zhang, Ming Fan, Yuanzhe Li, Maosheng Xu, Lihua Li. [doi]
• Deep Learning approach predicting breast tumor response to neoadjuvant treatment using DCE-MRI volumes acquired before and after chemotherapyMohammed El Adoui, Mohamed Amine Larhmam, Stylianos Drisis, Mohammed Benjelloun. [doi]
• Metastatic lymph node analysis of colorectal cancer using quadruple-phase CT imagesKeisuke Bando, Ren Nishimoto, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Gen Iinuma. [doi]
• Vendor-independent soft tissue lesion detection using weakly supervised and unsupervised adversarial domain adaptationJoris van Vugt, Elena Marchiori, Ritse Mann, Albert Gubern-Mérida, Nikita Moriakov, Jonas Teuwen. 1095002 [doi]
• Detecting mammographically-occult cancer in women with dense breasts using deep convolutional neural network and Radon cumulative distribution transformJuhun Lee, Robert M. Nishikawa. 1095003 [doi]
• Reducing overfitting of a deep learning breast mass detection algorithm in mammography using synthetic imagesKenny H. Cha, Nicholas Petrick, Aria Pezeshk, Christian G. Graff, Diksha Sharma, Andreu Badal, Aldo Badano, Berkman Sahiner. 1095004 [doi]
• Deep learning for identifying breast cancer malignancy and false recalls: a robustness study on training strategyKadie Clancy, Lei Zhang, Aly A. Mohamed, Sarah S. Aboutalib, Wendie A. Berg, Shandong Wu. 1095005 [doi]
• Evaluating deep learning techniques for dynamic contrast-enhanced MRI in the diagnosis of breast cancerRachel Anderson, Hui Li, Yu Ji, Peifang Liu, Maryellen L. Giger. 1095006 [doi]
• Registration based detection and quantification of intracranial aneurysm growthZiga Bizjak, Tim Jerman, Bostjan Likar, Franjo Pernus, Aichi Chien, Ziga Spiclin. 1095007 [doi]
• Reliability of computer-aided diagnosis tools with multi-center MR datasets: impact of training protocolM. Bento, R. Souza, Marina Salluzzi, Richard Frayne. 1095008 [doi]
• Automatic multi-modality segmentation of gross tumor volume for head and neck cancer radiotherapy using 3D U-NetZhe Guo, Ning Guo, Kuang Gong, Quanzheng Li. 1095009 [doi]
• Automatic multi-organ segmentation in thorax CT images using U-Net-GANYang Lei, Yingzi Liu, Xue-dong, Sibo Tian, Tonghe Wang, Xiaojun Jiang, Kristin Higgins, Jonathan J. Beitler, David S. Yu, Tian Liu, Walter J. Curran, Yi Fang, Xiaofeng Yang. 1095010 [doi]
• Polyp segmentation and classification using predicted depth from monocular endoscopyFaisal Mahmood, Ziyun Yang, Richard Chen, Daniel Borders, Wenhao Xu, Nicholas J. Durr. 1095011 [doi]
• Computer-aided classification of colorectal polyps using blue-light and linked-color imagingThom Scheeve, Ramon-Michel Schreuder, Fons van der Sommen, Joep E. G. IJspeert, Evelien Dekker, Erik J. Schoon, Peter H. N. de With. 1095012 [doi]
• Ensemble 3D residual network (E3D-ResNet) for reduction of false-positive polyp detections in CT colonographyTomoki Uemura, Janne J. Näppi, Huimin Lu, Hyoungseop Kim, Rie Tachibana, Toru Hironaka, Hiroyuki Yoshida. 1095013 [doi]
• A local geometrical metric-based model for polyp classificationWeiguo Cao, Marc J. Pomeroy, Perry J. Pickhardt, Matthew A. Barish, Samuel Stanly III, Zhengrong Liang. 1095014 [doi]
• Polyp-size classification with RGB-D features for colonoscopyHayato Itoh, Holger R. Roth, Yuichi Mori, Masashi Misawa, Masahiro Oda, Shin-ei Kudo, Kensaku Mori. 1095015 [doi]
• Handling label noise through model confidence and uncertainty: application to chest radiograph classificationErdi Calli, Ecem Sogancioglu, Ernst Th. Scholten, Keelin Murphy, Bram van Ginneken. 1095016 [doi]
• Classification of chest CT using case-level weak supervisionRuixiang Tang, Fakrul Islam Tushar, Songyue Han, Rui Hou, Geoffrey D. Rubin, Joseph Y. Lo. 1095017 [doi]
• Deep adversarial one-class learning for normal and abnormal chest radiograph classificationYuXing Tang, Youbao Tang, Mei Han, Jing Xiao, Ronald M. Summers. 1095018 [doi]
• Image biomarkers for quantitative analysis of idiopathic interstitial pneumoniaYoung-Wouk Kim, Sebastián Roberto Tarando, Pierre-Yves Brillet, Catalin I. Fetita. 1095019 [doi]
• Homogenization of breast MRI across imaging centers and feature analysis using unsupervised deep embeddingRavi K. Samala, Heang-Ping Chan, Lubomir M. Hadjiiski, Chintana Paramagul, Mark A. Helvie, Colleen H. Neal. 1095020 [doi]
• Shape variation analyzer: a classifier for temporomandibular joint damaged by osteoarthritisNina Tubau Ribera, Priscille de Dumast, Marilia Yatabe, Antonio C. Ruellas, Marcos Ioshida, Beatriz Paniagua, Martin Styner, João Roberto Gonçalves, Jonas Bianchi, Lucia H. S. Cevidanes, Juan-Carlos Prieto. 1095021 [doi]
• Automatic detection and localization of bone erosion in hand HR-pQCTJintao Ren, Arash Moaddel H., Ellen M. Hauge, Kresten K. Keller, Rasmus K. Jensen, François Lauze. 1095022 [doi]
• Spinal Vertebrae Segmentation and Localization by Transfer LearningJiashi Zhao, Zhengang Jiang, Kensaku Mori, Liyuan Zhang, Wei He, Weili Shi, Yu Miao, Fei Yan 0002, Fei He. 1095023 [doi]
• Ensembles of sparse classifiers for osteoporosis characterization in digital radiographsKeni Zheng, Rachid Jennane, Sokratis Makrogiannis. 1095024 [doi]
• Multiclass vertebral fracture classification using ensemble probability SVM with multi-feature selectionLiyuan Zhang, Jiashi Zhao, Huamin Yang, Weili Shi, Yu Miao, Fei He, Wei He, Yanfang Li, Ke Zhang, Kensaku Mori, Zhengang Jiang. 1095025 [doi]
• Cranial localization in 2D cranial ultrasound images using deep neural networksPooneh R. Tabrizi, Awais Mansoor, Rawad Obeid, Anna A. Penn, Marius George Linguraru. 1095026 [doi]
• Learning imbalanced semantic segmentation through cross-domain relations of multi-agent generative adversarial networksMina Rezaei, Haojin Yang, Christoph Meinel. 1095027 [doi]
• Spatial and depth weighted neural network for diagnosis of Alzheimer's diseaseQingfeng Li, Quan Huo, Xiaodan Xing, Yiqiang Zhan, Xiang Sean Zhou, Feng Shi. 1095028 [doi]
• Study on discrimination of Alzheimer's disease states using an ensemble neural network's modelJunsik Eom, Hanbyol Jang, Sewon Kim, Jinseong Jang, Dosik Hwang. 1095029 [doi]
• Longitudinal matching of in vivo adaptive optics images of fluorescent cells in the human eye using stochastically consistent superpixelsJianfei Liu, Haewon Jung, Tao Liu, Johnny Tam. 1095030 [doi]
• Computer-based detection of age-related macular degeneration and glaucoma using retinal images and clinical dataVinayak Joshi, Jeffrey Wigdahl, Jeremy Benson, Sheila C. Nemeth, Peter Soliz. 1095031 [doi]
• Fully-automated segmentation of optic disk from retinal images using deep learning techniquesFatemeh Zabihollahy, Eranga Ukwatta. 1095032 [doi]
• Deep learning-based detection of anthropometric landmarks in 3D infants head modelsHelena R. Torres, Bruno Oliveira 0002, Fernando Veloso, Mario Ruediger, Wolfram Burkhardt, António H. J. Moreira, Nuno Dias, Pedro Morais, Jaime C. Fonseca, João L. Vilaça. 1095034 [doi]
• Quantitative evaluation of local head malformations from 3 dimensional photography: application to craniosynostosisLiyun Tu, Antonio R. Porras, Albert Oh, Natasha Leporé, Graham C. Buck, Deki Tsering, Andinet Enquobahrie, Robert T. Keating, Gary F. Rogers, Marius George Linguraru. 1095035 [doi]
• Predicting resection volumes within the nasal cavity to improve patients breathingManuel Berger, Martin Pillei, Andreas H. Mehrle, Wolfgang Recheis, Florian Kral, Michael Kraxner, Wolfgang Freysinger. 1095036 [doi]
• Automated scoring of aortic calcification in vertebral fracture assessment imagesLuke Chaplin, Tim Cootes. 1095038 [doi]
• Detection and classification of coronary artery calcifications in low dose thoracic CT using deep learningJordan Fuhrman, Jennie Crosby, Rowena Yip, Claudia I. Henschke, David F. Yankelevitz, Maryellen L. Giger. 1095039 [doi]
• Radiomics analysis on T2-MR image to predict lymphovascular space invasion in cervical cancerShou Wang, Xi Chen, Zhenyu Liu, Qingxia Wu, Yongbei Zhu, Meiyun Wang, Jie Tian. 1095040 [doi]
• Temporal mammographic registration for evaluation of architecture changes in cancer risk assessmentKayla R. Mendel, Hui Li 0024, Nabihah Tayob, Randa El-Zein, Isabelle Bedrosian, Maryellen L. Giger. 1095041 [doi]
• PI-RADS guided discovery radiomics for characterization of prostate lesions with diffusion-weighted MRIFarzad Khalvati, Yucheng Zhang, Phuong H. U. Le, Isha Gujrathi, Masoom A. Haider. 1095042 [doi]
• Non-invasive transcriptomic classification of de novo Glioblastoma patients through multivariate quantitative analysis of baseline preoperative multimodal magnetic resonance imagingSaima Rathore, Hamed Akbari, Spyridon Bakas, Jared Pisapia, Xiao Da, Donald M. O'Rourke, Christos Davatzikos. 1095043 [doi]
• Radiomics analysis of MRI for predicting molecular subtypes of breast cancer in young womenQinmei Li, James D. Dormer, Priyanka Daryani, Deji Chen, Zhenfeng Zhang, Baowei Fei. 1095044 [doi]
• General purpose radiomics for multi-modal clinical researchMichael G. Wels, Félix Lades, Alexander Muehlberg, Michael Sühling. 1095046 [doi]
• Quantitative MRI biomarker for treatment response assessment of multiple myeloma: robustness evaluation using independent test set of prospective casesChuan Zhou, Qian Dong, Heang-Ping Chan, Erica L. Campagnaro, Jun Wei 0002, Lubomir M. Hadjiiski. 1095047 [doi]
• Machine-learning-based classification of Glioblastoma using MRI-based radiomic featuresGe Cui, Jiwoong Jason Jeong, Yang Lei, Tonghe Wang, Tian Liu, Walter J. Curran, Hui Mao, Xiaofeng Yang. 1095048 [doi]
• Prediction of low-grade glioma progression using MR imagingZeina A. Shboul, Khan M. Iftekharuddin. 1095049 [doi]