Ashirbani Saha

45 papers B 2Misc 2Journal 25Unranked 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Benchmarking domain-specific pretrained language models to identify the best model for methodological rigor in clinical studies. J. Biomed. Informatics Fangwen Zhou, Rick Parrish, Muhammad Afzal, Ashirbani Saha, R. Brian Haynes, Alfonso Iorio, Cynthia Lokker
2025	J	`jnl`	Externally Validated Multi-Task Learning via Consistency Regularization Using Differentiable BI-RADS Features for Breast Ultrasound Tumor Segmentation. CoRR Jingru Zhang, Saed Moradi, Ashirbani Saha
2025	—	`conf`	Multi-Distribution Mammogram Classification: Leveraging Clip for Enhanced Generalization Across Diverse Datasets. ISBI Zhichen Yan, Wandong Zhang, Yimin Yang, Ashirbani Saha
2025	J	`jnl`	Reporting guideline for chatbot health advice studies: The CHART statement. Artif. Intell. Medicine Bright Huo, Gary S. Collins, David Chartash, Arun Thirunavukarasu, Annette Flanagin, Alfonso Iorio, Giovanni E. Cacciamani, Xi Chen, Nan Liu, Piyush Mathur, An-Wen Chan, Christine Laine, Daniela Pacella, Michael Berkwits, Stavros A. Antoniou, Jennifer C. Camaradou, Carolyn Canfield, Michael Mittelman, Timothy Feeney, Elizabeth Loder, Riaz Agha, Ashirbani Saha, Julio Mayol, Anthony Sunjaya, Hugh Harvey, Jeremy Y. Ng, Tyler McKechnie, Yung Lee, Nipun Verma, Gregor Stiglic, Melissa McCradden, Karim Ramji, Vanessa Boudreau, Monica Ortenzi, Joerg Meerpohl, Per Olav Vandvik, Thomas Agoritsas, Diana Samuel, Helen Frankish, Michael Anderson, Xiaomei Yao, Stacy Loeb, Cynthia Lokker, Xiaoxuan Liu, Eliseo Guallar, Gordon Henry Guyatt
2025	—	`conf`	Visual Prompting and Adaptation of Vision Language Models for Tumor Classification in Breast Ultrasound. ISBI Ashirbani Saha, Dibyendu Mukherjee
2024	J	`jnl`	Measurement of adverse cosmesis in breast cancer: A deep learning approach. Expert Syst. Appl. Ashirbani Saha, Mark Levine, Isaac Kong, Elena Parvez, Timothy Whelan
2023	J	`jnl`	Performance of externally validated machine learning models based on histopathology images for the diagnosis, classification, prognosis, or treatment outcome prediction in female breast cancer: A systematic review. CoRR Ricardo Gonzalez, Peyman Nejat, Ashirbani Saha, Clinton J. V. Campbell, Andrew P. Norgan, Cynthia Lokker
2023	J	`jnl`	Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities. CoRR Ricardo Gonzalez, Ashirbani Saha, Clinton J. V. Campbell, Peyman Nejat, Cynthia Lokker, Andrew P. Norgan
2020	J	`jnl`	Detection of masses and architectural distortions in digital breast tomosynthesis: a publicly available dataset of 5, 060 patients and a deep learning model. CoRR Mateusz Buda, Ashirbani Saha, Ruth Walsh, Sujata V. Ghate, Nianyi Li, Albert Swiecicki, Joseph Y. Lo, Maciej A. Mazurowski
2020	—	`conf`	Generative adversarial network-based image completion to identify abnormal locations in digital breast tomosynthesis images. Computer-Aided Diagnosis Albert Swiecicki, Mateusz Buda, Ashirbani Saha, Nianyi Li, Sujata V. Ghate, Ruth Walsh, Maciej A. Mazurowski
2020	J	`jnl`	Machine learning applications using diffusion tensor imaging of human brain: A PubMed literature review. CoRR Ashirbani Saha, Pantea Fadaiefard, Jessica E. Rabski, Alireza Sadeghian, Michael D. Cusimano
2019	J	`jnl`	Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm. Comput. Biol. Medicine Mateusz Buda, Ashirbani Saha, Maciej A. Mazurowski
2019	J	`jnl`	Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm. CoRR Mateusz Buda, Ashirbani Saha, Maciej A. Mazurowski
2019	J	`jnl`	Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ. Comput. Biol. Medicine Zhe Zhu, Michael R. Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, Eun-Sil Shelley Hwang, Maciej A. Mazurowski
2019	J	`jnl`	Deep learning for identifying radiogenomic associations in breast cancer. Comput. Biol. Medicine Zhe Zhu, Ehab AlBadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski
2019	J	`jnl`	Hierarchical Convolutional Neural Networks for Segmentation of Breast Tumors in MRI With Application to Radiogenomics. IEEE Trans. Medical Imaging Jun Zhang, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski
2018	—	`conf`	Association of high proliferation marker Ki-67 expression with DCEMR imaging features of breast: a large scale evaluation. Computer-Aided Diagnosis Ashirbani Saha, Michael R. Harowicz, Lars J. Grimm, Connie E. Kim, Ruth Walsh, Sujata V. Ghate, Maciej A. Mazurowski
2018	J	`jnl`	Automatic deep learning-based normalization of breast dynamic contrast-enhanced magnetic resonance images. CoRR Jun Zhang, Ashirbani Saha, Brian J. Soher, Maciej A. Mazurowski
2018	—	`conf`	Breast cancer molecular subtype classification using deep features: preliminary results. Computer-Aided Diagnosis Zhe Zhu, Ehab AlBadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski
2018	—	`conf`	Breast mass detection in mammography and tomosynthesis via fully convolutional network-based heatmap regression. Computer-Aided Diagnosis Jun Zhang, Elizabeth Hope Cain, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski
2018	—	`conf`	Breast tumor segmentation in DCE-MRI using fully convolutional networks with an application in radiogenomics. Computer-Aided Diagnosis Jun Zhang, Ashirbani Saha, Zhe Zhu, Maciej A. Mazurowski
2018	—	`conf`	Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis. Computer-Aided Diagnosis Jun Zhang, Sujata V. Ghate, Lars J. Grimm, Ashirbani Saha, Elizabeth Hope Cain, Zhe Zhu, Maciej A. Mazurowski
2018	J	`jnl`	Deep learning in radiology: an overview of the concepts and a survey of the state of the art. CoRR Maciej A. Mazurowski, Mateusz Buda, Ashirbani Saha, Mustafa R. Bashir
2018	—	`conf`	Deep learning-based features of breast MRI for prediction of occult invasive disease following a diagnosis of ductal carcinoma in situ: preliminary data. Computer-Aided Diagnosis Zhe Zhu, Michael R. Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, Eun-Sil Shelley Hwang, Maciej A. Mazurowski
2017	J	`jnl`	Deep Learning for identifying radiogenomic associations in breast cancer. CoRR Zhe Zhu, Ehab AlBadawy, Ashirbani Saha, Jun Zhang, Michael R. Harowicz, Maciej A. Mazurowski
2017	J	`jnl`	Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ. CoRR Zhe Zhu, Michael R. Harowicz, Jun Zhang, Ashirbani Saha, Lars J. Grimm, Eun-Sil Shelley Hwang, Maciej A. Mazurowski
2017	—	`conf`	Deep learning for segmentation of brain tumors: can we train with images from different institutions? Computer-Aided Diagnosis David Paredes, Ashirbani Saha, Maciej A. Mazurowski
2017	J	`jnl`	Effects of MRI scanner parameters on breast cancer radiomics. Expert Syst. Appl. Ashirbani Saha, Xiaozhi Yu, Dushyant Sahoo, Maciej A. Mazurowski
2017	—	`conf`	Radiogenomic analysis of lower grade glioma: a pilot multi-institutional study shows an association between quantitative image features and tumor genomics. Computer-Aided Diagnosis Maciej A. Mazurowski, Kal Clark, Nicholas M. Czarnek, Parisa Shamsesfandabadi, Katherine B. Peters, Ashirbani Saha
2016	J	`jnl`	Full-reference image quality assessment by combining global and local distortion measures. Signal Process. Ashirbani Saha, Q. M. Jonathan Wu
2015	—	`—`	Investigating Potential Combinations of Visual Features towards Improvement of Full-Reference and No-Reference Image Quality Assessment. Ashirbani Saha
2015	J	`jnl`	Utilizing Image Scales Towards Totally Training Free Blind Image Quality Assessment. IEEE Trans. Image Process. Ashirbani Saha, Qingming Jonathan Wu
2014	J	`jnl`	Analysis and extension of multiresolution singular value decomposition. Inf. Sci. Gaurav Bhatnagar, Ashirbani Saha, Q. M. Jonathan Wu, Pradeep K. Atrey
2014	B	`conf`	Dual Gaussian mixture model with pixel history for background suppression. SMC Dibyendu Mukherjee, Ashirbani Saha, Q. M. Jonathan Wu, Wei Jiang
2014	J	`jnl`	Full-reference image quality assessment by combining global and local distortion measures. CoRR Ashirbani Saha, Q. M. Jonathan Wu
2014	J	`jnl`	High Frequency Content based Stimulus for Perceptual Sharpness Assessment in Natural Images. CoRR Ashirbani Saha, Q. M. Jonathan Wu
2014	B	`conf`	Multimodal 3D histogram for moving object detection. SMC Dibyendu Mukherjee, Ashirbani Saha, Q. M. Jonathan Wu, Wei Jiang
2013	Misc	`conf`	A study on using spectral saliency detection approaches for image quality assessment. ICASSP Ashirbani Saha, Q. M. Jonathan Wu
2013	J	`jnl`	Mutual spectral residual approach for multifocus image fusion. Digit. Signal Process. Ashirbani Saha, Gaurav Bhatnagar, Q. M. Jonathan Wu
2013	J	`jnl`	Perceptual image quality assessment using phase deviation sensitive energy features. Signal Process. Ashirbani Saha, Q. M. Jonathan Wu
2012	—	`conf`	Multiresolution based sigma-delta for motion segmentation. ITSC Dibyendu Mukherjee, Ashirbani Saha, Q. M. Jonathan Wu
2012	—	`conf`	SVD Filter Based Multiscale Approach for Image Quality Assessment. ICME Workshops Ashirbani Saha, Gaurav Bhatnagar, Q. M. Jonathan Wu
2010	—	`conf`	Curvelet Entropy for Facial Expression Recognition. PCM (2) Ashirbani Saha, Q. M. Jonathan Wu
2010	Misc	`conf`	Facial expression recognition using curvelet based local binary patterns. ICASSP Ashirbani Saha, Q. M. Jonathan Wu
2009	—	`conf`	A cost effective probabilistic approach to localization and mapping. EIT Dibyendu Mukherjee, Ashirbani Saha, Pankajkumar Mendapara, Dan Wu, Q. M. Jonathan Wu