Table of Contents

• Radiation-free quantification of head malformations in craniosynostosis patients from 3D photographyLiyun Tu, Antonio R. Porras, Albert Oh, Natasha Lepore, Manuel Mastromanolis, Deki Tsering, Beatriz Paniagua, Andinet Enquobahrie, Robert T. Keating, Gary F. Rogers, Marius George Linguraru. [doi]
• MRI textures as outcome predictor for Gamma Knife radiosurgery on vestibular schwannomaP. P. J. H. Langenhuizen, M. J. W. Legters, Svitlana Zinger, H. B. Verheul, S. Leenstra, Peter H. N. de With. [doi]
• Bladder cancer treatment response assessment with radiomic, clinical and radiologist semantic featuresMarshall N. Gordon, Kenny H. Cha, Lubomir M. Hadjiiski, Heang-Ping Chan, Richard H. Cohan, Elaine M. Caoili, Chintana Paramagul, Ajjai Alva, Alon Z. Weizer. [doi]
• Classification of brain MRI with big data and deep 3D convolutional neural networksViktor Wegmayr, Sai Aitharaju, Joachim M. Buhmann. [doi]
• Measurement of hard tissue density based on image density of intraoral radiographAkitoshi Katsumata, Tatsumasa Fukui, Shinji Shimoda, Kaoru Kobayashi, Tatsuro Hayashi. [doi]
• Temporal assessment of radiomic features on clinical mammography in a high-risk populationKayla R. Mendel, Hui Li, Li Lan, Chun-Wai Chan, Lauren M. King, Nabihah Tayob, Gary Whitman, Randa El-Zein, Isabelle Bedrosian, Maryellen L. Giger. [doi]
• Transfer learning with convolutional neural networks for lesion classification on clinical breast tomosynthesisKayla R. Mendel, Hui Li, Deepa Sheth, Maryellen L. Giger. [doi]
• A fully automatic microcalcification detection approach based on deep convolution neural networkGuanxiong Cai, Yanhui Guo, Yaqin Zhang, Genggeng Qin, Yuanpin Zhou, Yao Lu. [doi]
• Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learningBibo Shi, Rui Hou, Maciej A. Mazurowski, Lars J. Grimm, Yinhao Ren, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, E. Shelley Hwang, Joseph Y. Lo. [doi]
• Stability of deep features across CT scanners and field of view using a physical phantomRahul Paul, Muhammad Shafiq-ul-Hassan, Eduardo G. Moros, Robert J. Gillies, Lawrence O. Hall, Dmitry B. Goldgof. [doi]
• Impact of deep learning on the normalization of reconstruction kernel effects in imaging biomarker quantification: a pilot study in CT emphysemaHyeong-min Jin, Changyong Heo, Jong Hyo Kim. [doi]
• Reduction of false-positives in a CAD scheme for automated detection of architectural distortion in digital mammographyHelder Cesar Rodigues de Oliveira, Arianna Mencattini, Paola Casti, Eugenio Martinelli, Corrado Di Natale, Juliana H. Catani, Nestor de Barros, Carlos F. E. Melo, Adilson Gonzaga, Marcelo A. C. Vieira. [doi]
• Similarity estimation for reference image retrieval in mammograms using convolutional neural networkChisako Muramatsu, Shunichi Higuchi, Takako Morita, Mikinao Oiwa, Hiroshi Fujita 0001. [doi]
• Automated quasi-3D spine curvature quantification and classificationRupal Khilari, Juris Puchin, Kazunori Okada. [doi]
• Detection of eardrum abnormalities using ensemble deep learning approachesÇaglar Senaras, Aaron C. Moberly, Theodoros Teknos, Garth Essig, Charles Elmaraghy, Nazhat Taj-Schaal, Lianbo Yua, Metin N. Gurcan. [doi]
• Prognostic importance of pleural attachment status measured by pretreatment CT images in patients with stage IA lung adenocarcinoma: Measurement of the ratio of the interface between nodule and neighboring pleura to nodule surface areaYoshiki Kawata, Noboru Niki, Masahiko Kusumoto, Hironobu Ohmatsu, K. Aokage, G. Ishii, Y. Matsumoto, Takaaki Tsuchida, Kenji Eguchi, M. Kaneko. [doi]
• Quantitative analysis of adipose tissue on chest CT to predict primary graft dysfunction in lung transplant recipients: a novel optimal biomarker approachYubing Tong, Jayaram K. Udupa, Chuang Wang, Caiyun Wu, Gargi Pednekar, Michaela D. Restivo, David J. Lederer, Jason D. Christie, Drew A. Torigian. [doi]
• Pectoral muscle segmentation in breast tomosynthesis with deep learningAlejandro Rodriguez-Ruiz, Jonas Teuwen, Kaman Chung, Nico Karssemeijer, Margarita Chevalier, Albert Gubern-Mérida, Ioannis Sechopoulos. [doi]
• Breast cancer molecular subtype classification using deep features: preliminary resultsZhe Zhu, Ehab Albadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski. [doi]
• Performance evaluation of 2D and 3D deep learning approaches for automatic segmentation of multiple organs on CT imagesXiangrong Zhou, Kazuma Yamada, Takuya Kojima, Ryosuke Takayama, Song Wang, Xinxin Zhou, Takeshi Hara, Hiroshi Fujita 0001. [doi]
• Deep radiomic prediction with clinical predictors of the survival in patients with rheumatoid arthritis-associated interstitial lung diseasesRadin A. Nasirudin, Janne J. Näppi, Chinatsu Watari, Mikio Matsuhiro, Toru Hironaka, Shoji Kido, Hiroyuki Yoshida. [doi]
• Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football playersGowtham Krishnan Murugesan, Behrouz Saghafi, Elizabeth M. Davenport, Benjamin C. Wagner, Jillian Urban-Hobson, Mireille Kelley, Derek Jones, Alex Powers, Christopher T. Whitlow, Joel D. Stitzel, Joseph A. Maldjian, Albert Montillo. [doi]
• Classification of brain tumors using texture based analysis of T1-post contrast MR scans in a preclinical modelTien T. Tang, Janice A. Zawaski, Kathleen N. Francis, Amina A. Qutub, M. Waleed Gaber. [doi]
• Applying a new unequally weighted feature fusion method to improve CAD performance of classifying breast lesionsAbolfazl Zargari Khuzani, Gopichandh Danala, Morteza Heidari, Yue Du, Najmeh Mashhadi, Yuchen Qiu, Bin Zheng. [doi]
• Detection of brain tumor margins using optical coherence tomographyRonald M. Juarez-Chambi, Carmen Kut, Jesus Rico-Jimenez, Daniel U. Campos-Delgado, Alfredo Quinones-Hinojosa, Xingde Li, Javier A. Jo. [doi]
• A coarse-to-fine approach for pericardial effusion localization and segmentation in chest CT scansJiamin Liu, Karthik Chellamuthu, Le Lu, Mohammadhadi Bagheri, Ronald M. Summers. [doi]
• Deep learning in breast cancer risk assessment: evaluation of fine-tuned convolutional neural networks on a clinical dataset of FFDMsHui Li, Kayla R. Mendel, John H. Lee, Li Lan, Maryellen L. Giger. [doi]
• Association between mammogram density and background parenchymal enhancement of breast MRIFaranak Aghaei, Gopichandh Danala, Yunzhi Wang, Ali Zarafshani, Wei Qian, Hong Liu, Bin Zheng. [doi]
• Automatic pedicles detection using convolutional neural network in a 3D spine reconstruction from biplanar radiographsChristine Bakhous, Benjamin Aubert, Carlos Vazquez, Thierry Cresson, Stefan Parent, Jacques A. de Guise. [doi]
• Lung parenchymal analysis on dynamic MRI in thoracic insufficiency syndrome to assess changes following surgical interventionBasavaraj N. Jagadale, Jayaram K. Udupa, Yubing Tong, Caiyun Wu, Joseph M. McDonough, Drew A. Torigian, Robert M. Campbell Jr.. [doi]
• Quantitative CT based radiomics as predictor of resectability of pancreatic adenocarcinomaJoost van der Putten, Svitlana Zinger, Fons van der Sommen, Peter H. N. de With, Mathias Prokop, John Hermans. [doi]
• Saliency U-Net: A regional saliency map-driven hybrid deep learning network for anomaly segmentationAlex Karargyros, Tanveer F. Syeda-Mahmood. [doi]
• Quantitative characterization of liver tumor radiodensity in CT images: a phantom study between two scannersBenjamin Paul Berman, Qin Li, Sarah McKenney, Stanley Thomas Fricke, Yuan Fang, Marios A. Gavrielides, Nicholas Petrick. [doi]
• Robustness of radiomic breast features of benign lesions and luminal A cancers across MR magnet strengthsHeather M. Whitney, Karen Drukker, Alexandra Edwards, John Papaioannou, Maryellen L. Giger. [doi]
• Applying a new mammographic imaging marker to predict breast cancer riskFaranak Aghaei, Gopichandh Danala, Alan B. Hollingsworth, Rebecca G. Stough, Melanie Pearce, Hong Liu, Bin Zheng. [doi]
• Deep 3D convolution neural network for CT brain hemorrhage classificationKamal Jnawali, Mohammad R. Arbabshirani, Navalgund Rao, Alpen A. Patel. [doi]
• Automatic detection of kidney in 3D pediatric ultrasound images using deep neural networksPooneh R. Tabrizi, Awais Mansoor, Elijah Biggs, James Jago, Marius George Linguraru. [doi]
• Fully automated bone mineral density assessment from low-dose chest CTShuang Liu, Jessica González, Javier Zulueta, Juan P. de-Torres, David F. Yankelevitz, Claudia I. Henschke, Anthony P. Reeves. [doi]
• Deep-learning derived features for lung nodule classification with limited datasetsPhawis Thammasorn, W. Wu, L. A. Pierce, S. N. Pipavath, P. D. Lampe, A. M. Houghton, D. R. Haynor, W. Art Chaovalitwongse, Paul E. Kinahan. [doi]
• Bladder cancer treatment response assessment in CT urography using two-channel deep-learning networkKenny H. Cha, Lubomir M. Hadjiiski, Heang-Ping Chan, Ravi K. Samala, Richard H. Cohan, Elaine M. Caoili, Alon Z. Weizer, Ajjai Alva. [doi]
• Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networksBehrouz Saghafi, Gowtham Murugesan, Elizabeth M. Davenport, Benjamin C. Wagner, Jillian Urban, Mireille Kelley, Derek Jones, Alexander Powers, Christopher T. Whitlow, Joel D. Stitzel, Joseph A. Maldjian, Albert Montillo. [doi]
• Cross-domain and multi-task transfer learning of deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesisRavi K. Samala, Heang-Ping Chan, Lubomir M. Hadjiiski, Mark A. Helvie, Caleb Richter, Kenny H. Cha. [doi]
• Breast tumor segmentation in DCE-MRI using fully convolutional networks with an application in radiogenomicsJun Zhang, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski. [doi]
• Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary dataZhe Zhu, Michael R. Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, E. Shelley Hwang, Maciej A. Mazurowski. [doi]
• Segmentation of skin lesions in chronic graft versus host disease photographs with fully convolutional networksJianing Wang, Fuyao Chen, Laura E. Dellalana, Madan H. Jagasia, Eric R. Tkaczyk, Benoit M. Dawant. [doi]
• Improving performance of breast cancer risk prediction using a new CAD-based region segmentation schemeMorteza Heidari, Abolfazl Zargari Khuzani, Gopichandh Danala, Yuchen Qiu, Bin Zheng. [doi]
• Asymmetry quantification from reflectance images of orthotic patients using structural similarity metricsMarc-Antoine Boucher, Nicolas Watts, Frederic Gremillet, Philippe Legare, Samuel Kadoury. [doi]
• Myocardial scar segmentation from magnetic resonance images using convolutional neural networkFatemeh Zabihollahy, James A. White, Eranga Ukwatta. [doi]
• Automated synovium segmentation in doppler ultrasound images for rheumatoid arthritis assessmentPak-Hei Yeung, York-Kiat Tan, Shuoyu Xu. [doi]
• Quantitative image feature variability amongst CT scanners with a controlled scan protocolRachel B. Ger, Shouhao Zhou, Pai-Chun Melinda Chi, David L. Goff, Lifei Zhang, Hannah J. Lee, Clifton D. Fuller, Rebecca M. Howell, Heng Li, R. Jason Stafford, Laurence E. Court, Dennis S. Mackin. [doi]
• Anomaly detection for medical images based on a one-class classificationQi Wei, Yinhao Ren, Rui Hou, Bibo Shi, Joseph Y. Lo, Lawrence Carin. [doi]
• A quality score for coronary artery tree extraction resultsQing Cao, Alexander Broersen, Pieter H. Kitslaar, Boudewijn P. F. Lelieveldt, Jouke Dijkstra. [doi]
• Empirical evaluation of cross-site reproducibility in radiomic features for characterizing prostate MRIPrathyush Chirra, Patrick Leo, Michael Yim, B. Nicolas Bloch, Ardeshir R. Rastinehad, Andrei Purysko, Mark Rosen, Anant Madabhushi, Satish Viswanath. [doi]
• Variations in algorithm implementation among quantitative texture analysis software packagesJoseph J. Foy, Prerana Mitta, Lauren R. Nowosatka, Kayla R. Mendel, Hui Li, Maryellen L. Giger, Hania A. Al-Hallaq, Samuel G. Armato III. [doi]
• Improving classification with forced labeling of other related classes: application to prediction of upstaged ductal carcinoma in situ using mammographic featuresRui Hou, Bibo Shi, Lars J. Grimm, Maciej A. Mazurowski, Jeffrey R. Marks, Lorraine M. King, Carlo C. Maley, E. Shelley Hwang, Joseph Y. Lo. [doi]
• Evaluation of a deep learning architecture for MR imaging prediction of ATRX in glioma patientsPanagiotis Korfiatis, Timothy L. Kline, Bradley J. Erickson. [doi]
• Applying a CAD-generated imaging marker to assess short-term breast cancer riskSeyedehnafiseh Mirniaharikandehei, Ali Zarafshani, Morteza Heidari, Yunzhi Wang, Faranak Aghaei, Bin Zheng. [doi]
• Deep learning and texture-based semantic label fusion for brain tumor segmentationL. Vidyaratne, Mahbubul Alam, Zeina A. Shboul, Khan M. Iftekharuddin. [doi]
• Recurrent neural networks for breast lesion classification based on DCE-MRIsNatasha Antropova, Benjamin Q. Huynh, Maryellen L. Giger. [doi]
• A deep learning classifier for prediction of pathological complete response to neoadjuvant chemotherapy from baseline breast DCE-MRIKavya Ravichandran, Nathaniel Braman, Andrew Janowczyk, Anant Madabhushi. [doi]
• Automated volumetric lung segmentation of thoracic CT images using fully convolutional neural networkMohammadreza Negahdar, David Beymer, Tanveer F. Syeda-Mahmood. [doi]
• Identification and functional characterization of HIV-associated neurocognitive disorders with large-scale Granger causality analysis on resting-state functional MRIUdaysankar Chockanathan, Adora M. DSouza, Anas Z. Abidin, Giovanni Schifitto, Axel Wismüller. [doi]
• Radiomics for ultrafast dynamic contrast-enhanced breast MRI in the diagnosis of breast cancer: a pilot studyKaren Drukker, Rachel Anderson, Alexandra Edwards, John Papaioannou, Fred Pineda, Hiroyuki Abe, Gregory Karzcmar, Maryellen L. Giger. [doi]
• Computer aided detection system for Osteoporosis using low dose thoracic 3D CT imagesDaisuke Tsuji, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Yasutaka Nakano, Masafumi Harada, Masahiko Kusumoto, Takaaki Tsuchida, Kenji Eguchi, Masahiro Kaneko. [doi]
• Multi-resolution analysis using integrated microscopic configuration with local patterns for benign-malignant mass classificationRinku Rabidas, Abhishek Midya, Jayasree Chakraborty, Anup Sadhu, Wasim Arif. [doi]
• Classifying magnetic resonance image modalities with convolutional neural networksSamuel Remedios, Dzung L. Pham, John A. Butman, Snehashis Roy. [doi]
• Expert identification of visual primitives used by CNNs during mammogram classificationJimmy Wu, Diondra Peck, Scott Hsieh, Vandana Dialani, Constance D. Lehman, Bolei Zhou, Vasilis Syrgkanis, Lester W. Mackey, Genevieve Patterson. [doi]
• Comparing deep learning models for population screening using chest radiographyR. Sivaramakrishnan, Sameer K. Antani, Sema Candemir, Zhiyun Xue, Joseph Abuya, Marc D. Kohli, Philip Alderson, George R. Thoma. [doi]
• Automated volumetry of temporal horn of lateral ventricle for detection of Alzheimer's disease in CT scanNoriyuki Takahashi, Toshibumi Kinoshita, Tomomi Ohmura, Eri Matsuyama, Hideto Toyoshima. [doi]
• ADMultiImg: a novel missing modality transfer learning based CAD system for diagnosis of MCI due to AD using incomplete multi-modality imaging dataXiaonan Liu, Kewei Chen, Teresa Wu, David Weidman, Fleming Lure, Jing Li. [doi]
• Bladder cancer staging in CT urography: effect of stage labels on statistical modeling of a decision support systemDhanuj Gandikota, Lubomir M. Hadjiiski, Kenny H. Cha, Heang-Ping Chan, Elaine M. Caoili, Richard H. Cohan, Alon Z. Weizer, Ajjai Alva, Chintana Paramagul, Jun Wei 0002, Chuan Zhou. [doi]
• Comparison of machine learned approaches for thyroid nodule characterization from shear wave elastography imagesCarina Pereira, Manjiri Dighe, Adam M. Alessio. [doi]
• Deep convolutional neural network for mammographic density segmentationJun Wei 0002, Songfeng Li, Heang-Ping Chan, Mark A. Helvie, Marilyn A. Roubidoux, Yao Lu, Chuan Zhou, Lubomir M. Hadjiiski, Ravi K. Samala. [doi]
• Longitudinal connectome-based predictive modeling for REM sleep behavior disorder from structural brain connectivityLuca Giancardo, Timothy M. Ellmore, Jessika Suescun, Laura Ocasio, Arash Kamali, Roy Riascos-Castaneda, Mya C. Schiess. [doi]
• Quantitative CT analysis for the preoperative prediction of pathologic grade in pancreatic neuroendocrine tumorsJayasree Chakraborty, Alessandra Pulvirenti, Rikiya Yamashita, Abhishek Midya, Mithat Gönen, David S. Klimstra, Diane L. Reidy, Peter J. Allen, Richard K. G. Do, Amber L. Simpson. [doi]
• An automatically generated texture-based atlas of the lungsYashin Dicente Cid, Oula Puonti, Alexandra Platon, Koen Van Leemput, Henning Müller, Pierre-Alexandre Poletti. [doi]
• Quantitative assessment for pneumoconiosis severity diagnosis using 3D CT imagesKoki Hino, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Katsuya Kato, Takumi Kishimoto, Kazuto Ashizawa. [doi]
• Deformable image registration as a tool to improve survival prediction after neoadjuvant chemotherapy for breast cancer: results from the ACRIN 6657/I-SPY-1 trialNariman Jahani, Eric Cohen, Meng Kang Hsieh, Susan P. Weinstein, Lauren Pantalone, Christos Davatzikos, Despina Kontos. [doi]
• Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesisJun Zhang, Sujata V. Ghate, Lars J. Grimm, Ashirbani Saha, Elizabeth Hope Cain, Zhe Zhu, Maciej A. Mazurowski. [doi]
• Radiomic biomarkers from PET/CT multi-modality fusion images for the prediction of immunotherapy response in advanced non-small cell lung cancer patientsWei Mu, Jin Qi, Hong Lu, Matthew B. Schabath, Yoganand Balagurunathan, Ilke Tunali, Robert James Gillies. [doi]
• Automatic detection of anatomical regions in frontal x-ray images: comparing convolutional neural networks to random forestR. Olory Agomma, C. Vázquez, Thierry Cresson, Jacques A. de Guise. [doi]
• Histogram-based adaptive gray level scaling for texture feature classification of colorectal polypsMarc Pomeroy, Hongbing Lu, Perry J. Pickhardt, Zhengrong Liang. [doi]
• Using YOLO based deep learning network for real time detection and localization of lung nodules from low dose CT scansSindhu Ramachandran, Jose George, Shibon Skaria, Varun V. V.. [doi]
• Differentiating invasive and pre-invasive lung cancer by quantitative analysis of histopathologic imagesChuan Zhou, Hongliu Sun, Heang-Ping Chan, Aamer Chughtai, Jun Wei 0002, Lubomir M. Hadjiiski, Ella A. Kazerooni. [doi]
• Aortic root segmentation in 4D transesophageal echocardiographyShubham Chechani, Rahul Suresh, Kedar A. Patwardhan. [doi]
• Computer-aided classification of breast masses using contrast-enhanced digital mammogramsGopichandh Danala, Faranak Aghaei, Morteza Heidari, Teresa Wu, Bhavika Patel, Bin Zheng. [doi]
• Exploring DeepMedic for the purpose of segmenting white matter hyperintensity lesionsFiona Lippert, Bastian Cheng, Amir Golsari, Florian Weiler, Johannes Gregori, Götz Thomalla, Jan Klein 0001. [doi]
• Computer-aided detection of basal cell carcinoma through blood content analysis in dermoscopy imagesPegah Kharazmi, Sunil Kalia, Harvey Lui, Z. Jane Wang, Tim K. Lee. [doi]
• Automated assessment of aortic and main pulmonary arterial diameters using model-based blood vessel segmentation for predicting chronic thromboembolic pulmonary hypertension in low-Dose CT lung screeningHidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Toshihiko Sugiura, Nobuhiro Tanabe, Masahiko Kusumoto, Kenji Eguchi, Masahiro Kaneko. [doi]
• Voxel-based plaque classification in coronary intravascular optical coherence tomography images using decision treesChaitanya Kolluru, David Prabhu, Yazan Gharaibeh, Hao Wu, David L. Wilson. [doi]
• A primitive study on unsupervised anomaly detection with an autoencoder in emergency head CT volumesDaisuke Sato, Shouhei Hanaoka, Yukihiro Nomura, Tomomi Takenaga, Soichiro Miki, Takeharu Yoshikawa, Naoto Hayashi, Osamu Abe. [doi]
• Automated detection and segmentation of follicles in 3D ultrasound for assisted reproductionNikhil S. Narayan, Srinivasan Sivanandan, Srinivas Kudavelly, Kedar A. Patwardhan, G. A. Ramaraju. [doi]
• Towards quantitative imaging: stability of fully-automated nodule segmentation across varied dose levels and reconstruction parameters in a low-dose CT screening patient cohortM. Wasil Wahi-Anwar, Nastaran Emaminejad, John M. Hoffman, Grace H. Kim, Matthew S. Brown, Michael F. McNitt-Gray. [doi]
• Reduction in training time of a deep learning model in detection of lesions in CTNazanin Makkinejad, Nima Tajbakhsh, Amin Zarshenas, Ashfaq Khokhar, Kenji Suzuki. [doi]
• Urinary bladder cancer T-staging from T2-weighted MR images using an optimal biomarker approachChuang Wang, Jayaram K. Udupa, Yubing Tong, Jerry Chen, Sriram Venigalla, Dewey Odhner, Thomas J. Guzzo, John Christodouleas, Drew A. Torigian. [doi]
• Gaussian Processes with optimal kernel construction for neuro-degenerative clinical onset predictionLiane S. Canas, Benjamin C. Yvernault, David M. Cash, Erika Molteni, Tom Veale, Tammie L. Benzinger, Sébastien Ourselin, Simon Mead, Marc Modat. [doi]
• Dense volumetric detection and segmentation of mediastinal lymph nodes in chest CT imagesHirohisa Oda, Holger R. Roth, Kanwal K. Bhatia, Masahiro Oda, Takayuki Kitasaka, Shingo Iwano, Hirotoshi Honma, Hirotsugu Takabatake, Masaki Mori, Hiroshi Natori, Julia A. Schnabel, Kensaku Mori. 1057502 [doi]
• Early detection of lung cancer recurrence after stereotactic ablative radiation therapy: radiomics system designSalma Dammak, David A. Palma, Sarah A. Mattonen, Suresh Senan, Aaron D. Ward. 1057503 [doi]
• Pneumothorax detection in chest radiographs using convolutional neural networkAviel Blumenfeld, Eli Konen, Hayit Greenspan. 1057504 [doi]
• Boosting CNN performance for lung texture classification using connected filteringSebastian Roberto Tarando, Catalin I. Fetita, Young-Wouk Kim, Hyoun Cho, Pierre-Yves Brillet. 1057505 [doi]
• Automatic liver volume segmentation and fibrosis classificationEvgeny Bal, Eyal Klang, Michal Amitai, Hayit Greenspan. 1057506 [doi]
• Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: a large scale evaluationAshirbani Saha, Michael R. Harowicz, Lars J. Grimm, Connie E. Kim, Ruth Walsh, Sujata V. Ghate, Maciej A. Mazurowski. 1057507 [doi]
• Detecting mammographically-occult cancer in women with dense breasts using Radon Cumulative Distribution Transform: a preliminary analysisJuhun Lee, Robert M. Nishikawa, Gustavo K. Rohde. 1057508 [doi]
• Deriving stable multi-parametric MRI radiomic signatures in the presence of inter-scanner variations: survival prediction of glioblastoma via imaging pattern analysis and machine learning techniquesSaima Rathore, Spyridon Bakas, Hamed Akbari, Gaurav Shukla, Martin Rozycki, Christos Davatzikos. 1057509 [doi]
• Automated segmentation of geographic atrophy using deep convolutional neural networksZhihong Hu, Ziyuan Wang, SriniVas R. Sadda. 1057511 [doi]
• An affordable and easy-to-use diagnostic method for keratoconus detection using a smartphoneBehnam Askarian, Fatemehsadat Tabei, Amin Askarian, Jo Woon Chong. 1057512 [doi]
• Detection of protruding lesion in wireless capsule endoscopy videos of small intestineChengliang Wang, Zhuo Luo, Xiaoqi Liu, Jianying Bai, Guobin Liao. 1057513 [doi]
• Radiomics analysis of DWI data to identify the rectal cancer patients qualified for local excision after neoadjuvant chemoradiotherapyZhenchao Tang, Zhenyu Liu, Xiaoyan Zhang, Yanjie Shi, Shou Wang, Mengjie Fang, Yingshi Sun, Enqing Dong, Jie Tian. 1057514 [doi]
• Development of a computer aided diagnosis model for prostate cancer classification on multi-parametric MRIR. Alfano, D. Soetemans, Glenn S. Bauman, Eli Gibson, Mena Gaed, Madeleine Moussa, Jose A. Gomez, Joseph L. Chin, Stephen Pautler, Aaron D. Ward. 1057515 [doi]
• Cascade classification of endocytoscopic images of colorectal lesions for automated pathological diagnosisHayato Itoh, Yuichi Mori, Masashi Misawa, Masahiro Oda, Shin-ei Kudo, Kensaku Mori. 1057516 [doi]
• A new fractional order derivative based active contour model for colon wall segmentationBo Chen, Lihong C. Li, Huafeng Wang, Xinzhou Wei, Shan Huang, Wensheng Chen, Zhengrong Liang. 1057517 [doi]
• Detection of colorectal masses in CT colonography: application of deep residual networks for differentiating masses from normal colon anatomyJanne J. Näppi, Toru Hironaka, Hiroyuki Yoshida. 1057518 [doi]
• Comparison of different deep learning approaches for parotid gland segmentation from CT imagesAnnika Hänsch, Michael Schwier, Tobias Gass, Tomasz Morgas, Benjamin Haas, Jan Klein 0001, Horst K. Hahn. 1057519 [doi]
• Generalization error analysis: deep convolutional neural network in mammographyCaleb D. Richter, Ravi K. Samala, Heang-Ping Chan, Lubomir M. Hadjiiski, Kenny H. Cha. 1057520 [doi]
• Compression of deep convolutional neural network for computer-aided diagnosis of masses in digital breast tomosynthesisRavi K. Samala, Heang-Ping Chan, Lubomir M. Hadjiiski, Mark A. Helvie, Caleb Richter, Kenny H. Cha. 1057521 [doi]
• ICADx: interpretable computer aided diagnosis of breast massesSeong-Tae Kim, Hakmin Lee, Hak Gu Kim, Yong Man Ro. 1057522 [doi]
• Do pre-trained deep learning models improve computer-aided classification of digital mammograms?Sarah S. Aboutalib, Aly A. Mohamed, Margarita L. Zuley, Wendie A. Berg, Yahong Luo, Shandong Wu. 1057523 [doi]
• Fully automated gynecomastia quantification from low-dose chest CTShuang Liu, Emily B. Sonnenblick, Lea Azour, David F. Yankelevitz, Claudia I. Henschke, Anthony P. Reeves. 1057524 [doi]
• Breast mass detection in mammography and tomosynthesis via fully convolutional network-based heatmap regressionJun Zhang, Elizabeth Hope Cain, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski. 1057525 [doi]
• Detecting PHG frames in wireless capsule endoscopy video by integrating rough global dominate-color with fine local texture featureXiaoqi Liu, Chengliang Wang, Jianying Bai, Guobin Liao. 1057526 [doi]
• Automatic blood vessel based- liver segmentation using the portal phase abdominal CTAhmed S. Maklad, Mikio Matsuhiro, Hidenobu Suzuki, Yoshiki Kawata, Noboru Niki, Mitsuo Shimada, Gen Iinuma. 1057527 [doi]
• Deep convolutional neural network for the classification of hepatocellular carcinoma and intrahepatic cholangiocarcinomaAbhishek Midya, Jayasree Chakraborty, Linda M. Pak, Jian Zheng, William R. Jarnagin, Richard K. G. Do, Amber L. Simpson. 1057528 [doi]
• Computer-aided detection of bladder wall thickening in CT urography (CTU)Kenny H. Cha, Lubomir M. Hadjiiski, Heang-Ping Chan, Elaine M. Caoili, Richard H. Cohan, Alon Z. Weizer, Marshall N. Gordon, Ravi K. Samala. 1057529 [doi]
• Convolutional neural networks for the detection of diseased hearts using CT images and left atrium patchesJames D. Dormer, Martin T. Halicek, Ling Ma, Carolyn M. Reilly, Eduard Schreibmann, Baowei Fei. 1057530 [doi]
• Lesion detection in ultra-wide field retinal images for diabetic retinopathy diagnosisAnastasia Levenkova, Arcot Sowmya, Michael Kalloniatis, Angelica Ly, Arthur Ho. 1057531 [doi]
• 3D GGO candidate extraction in lung CT images using multilevel thresholding on supervoxelsShan Huang, Xiabi Liu, Guanghui Han, Xinming Zhao, Yanfeng Zhao, Chunwu Zhou. 1057533 [doi]
• Opacity annotation of diffuse lung diseases using deep convolutional neural network with multi-channel informationShingo Mabu, Shoji Kido, Noriaki Hashimoto, Yasushi Hirano, Takashi Kuremoto. 1057534 [doi]
• Localization of lung fields in HRCT images using a deep convolution neural networkAbhishek Kumar, Sunita Agarwala, Ashis Kumar Dhara, Debashis Nandi, Sudipta Mukhopadhyay, Mandeep Garg, Niranjan Khandelwal, Naveen Kalra. 1057535 [doi]
• Deep neural network convolution (NNC) for three-class classification of diffuse lung disease opacities in high-resolution CT (HRCT): Consolidation, ground-glass opacity (GGO), and normal opacityNoriaki Hashimoto, Kenji Suzuki, Junchi Liu, Yasushi Hirano, Heber MacMahon, Shoji Kido. 1057536 [doi]
• A deep-learning based automatic pulmonary nodule detection systemYiyuan Zhao, Liang Zhao, Zhennan Yan, Matthias Wolf 0001, Yiqiang Zhan. 1057537 [doi]
• An evaluation of consensus techniques for diagnostic interpretationJake N. Sauter, Victoria M. LaBarre, Jacob D. Furst, Daniela Stan Raicu. 1057538 [doi]
• Lung nodule detection from CT scans using 3D convolutional neural networks without candidate selectionNatalia M. Jenuwine, Sunny N. Mahesh, Jacob D. Furst, Daniela Stan Raicu. 1057539 [doi]