202 citations · 539 across the 30 of their papers we have counts for
36 papers
Representation geometry shapes task performance in vision-language modeling for CT enterography
Cristian Minoccheri, Emily Wittrup, Kayvan Najarian +1
Computed tomography (CT) enterography is a primary imaging modality for assessing inflammatory bowel disease (IBD), yet the representational choices that best support automated ana…
A Causal Machine Learning Framework for Treatment Personalization in Clinical Trials: Application to Ulcerative Colitis
Cristian Minoccheri, Sophia Tesic, Kayvan Najarian +1
Randomized controlled trials estimate average treatment effects, but treatment response heterogeneity motivates personalized approaches. A critical question is whether statisticall…
LISM: Long-range Integrative State space Models via Input-Latent State Interactions
Cong Ma, Kayvan Najarian, Hovhannes Baghdasaryan +1
State space models (SSMs) are an emerging paradigm that achieves linear-time scaling, however, they intrinsically suffer from "curse of memory". The memory of SSMs, including Mamba…
LoRA-based methods on Unet for transfer learning in Subarachnoid Hematoma Segmentation
Cristian Minoccheri, Matthew Hodgman, Haoyuan Ma +4
Aneurysmal subarachnoid hemorrhage (SAH) is a life-threatening neurological emergency with mortality rates exceeding 30%. Transfer learning from related hematoma types represents a…
Supervised Coupled Matrix-Tensor Factorization (SCMTF) for Computational Phenotyping of Patient Reported Outcomes in Ulcerative Colitis
Cristian Minoccheri, Sophia Tesic, Kayvan Najarian +1
Phenotyping is the process of distinguishing groups of patients to identify different types of disease progression. A recent trend employs low-rank matrix and tensor factorization…
Tensor Denoising via Amplification and Stable Rank Methods
Jonathan Gryak, Kayvan Najarian, Harm Derksen
Tensors in the form of multilinear arrays are ubiquitous in data science applications. Captured real-world data, including video, hyperspectral images, and discretized physical sys…
Prediction of Oral Food Challenge Outcomes via Ensemble Learning
Justin Zhang, Deborah Lee, Kylie Jungles +5
Oral Food Challenges (OFCs) are essential to accurately diagnosing food allergy due to the limitations of existing clinical testing. However, some patients are hesitant to undergo…
A Novel Tropical Geometry-based Interpretable Machine Learning Method: Application in Prognosis of Advanced Heart Failure
Heming Yao, Harm Derksen, Jessica R. Golbus +4
A model's interpretability is essential to many practical applications such as clinical decision support systems. In this paper, a novel interpretable machine learning method is pr…
Motion-based Camera Localization System in Colonoscopy Videos
Heming Yao, Ryan W. Stidham, Zijun Gao +2
Optical colonoscopy is an essential diagnostic and prognostic tool for many gastrointestinal diseases, including cancer screening and staging, intestinal bleeding, diarrhea, abdomi…
Radial basis function kernel optimization for Support Vector Machine classifiers
Karl Thurnhofer-Hemsi, Ezequiel López-Rubio, Miguel A. Molina-Cabello +1
Support Vector Machines (SVMs) are still one of the most popular and precise classifiers. The Radial Basis Function (RBF) kernel has been used in SVMs to separate among classes wit…
Algebraic Methods for Tensor Data
Neriman Tokcan, Jonathan Gryak, Kayvan Najarian +1
We develop algebraic methods for computations with tensor data. We give 3 applications: extracting features that are invariant under the orthogonal symmetries in each of the modes,…
Fetal Ultrasound Image Segmentation for Measuring Biometric Parameters Using Multi-Task Deep Learning
Zahra Sobhaninia, Shima Rafiei, Ali Emami +4
Ultrasound imaging is a standard examination during pregnancy that can be used for measuring specific biometric parameters towards prenatal diagnosis and estimating gestational age…
Gland Segmentation in Histopathology Images Using Deep Networks and Handcrafted Features
Safiyeh Rezaei, Ali Emami, Hamidreza Zarrabi +5
Histopathology images contain essential information for medical diagnosis and prognosis of cancerous disease. Segmentation of glands in histopathology images is a primary step for…
An Unsupervised Feature Learning Approach to Reduce False Alarm Rate in ICUs
Behzad Ghazanfari, Fatemeh Afghah, Kayvan Najarian +3
The high rate of false alarms in intensive care units (ICUs) is one of the top challenges of using medical technology in hospitals. These false alarms are often caused by patients'…
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy for Detection of Informative Frames
Mohsen Hajabdollahi, Reza Esfandiarpoor, Pejman Khadivi +4
Wireless capsule endoscopy (WCE) is an effective mean for diagnosis of gastrointestinal disorders. Detection of informative scenes in WCE video could reduce the length of transmitt…
Liver segmentation in CT images using three dimensional to two dimensional fully convolutional network
Shima Rafiei, Ebrahim Nasr-Esfahani, S. M. Reza Soroushmehr +3
The need for CT scan analysis is growing for pre-diagnosis and therapy of abdominal organs. Automatic organ segmentation of abdominal CT scan can help radiologists analyze the scan…
Left ventricle segmentation By modelling uncertainty in prediction of deep convolutional neural networks and adaptive thresholding inference
Alireza Norouzi, Ali Emami, S. M. Reza Soroushmehr +3
Deep neural networks have shown great achievements in solving complex problems. However, there are fundamental problems that limit their real world applications. Lack of measurable…
Low complexity convolutional neural network for vessel segmentation in portable retinal diagnostic devices
M. Hajabdollahi, R. Esfandiarpoor, S. M. R. Soroushmehr +3
Retinal vessel information is helpful in retinal disease screening and diagnosis. Retinal vessel segmentation provides useful information about vessels and can be used by physician…
Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization
Mohsen Hajabdollahi, Reza Esfandiarpoor, S. M. Reza Soroushmehr +3
Wireless capsule endoscopy (WCE) is an effective means of diagnosis of gastrointestinal disorders. Detection of informative scenes by WCE could reduce the length of transmitted vid…
Reversible Image Watermarking for Health Informatics Systems Using Distortion Compensation in Wavelet Domain
Hamidreza Zarrabi, Mohsen Hajabdollahi, S. M. Reza Soroushmehr +3
Reversible image watermarking guaranties restoration of both original cover and watermark logo from the watermarked image. Capacity and distortion of the image under reversible wat…
Lossless Image Compression Algorithm for Wireless Capsule Endoscopy by Content-Based Classification of Image Blocks
Atefe Rajaeefar, Ali Emami, S. M. Reza Soroushmehr +3
Recent advances in capsule endoscopy systems have introduced new methods and capabilities. The capsule endoscopy system, by observing the entire digestive tract, has significantly…
Left Ventricle Segmentation in Cardiac MR Images Using Fully Convolutional Network
Mina Nasr-Esfahani, Majid Mohrekesh, Mojtaba Akbari +5
Medical image analysis, especially segmenting a specific organ, has an important role in developing clinical decision support systems. In cardiac magnetic resonance (MR) imaging, s…
Lossless Compression of Angiogram Foreground with Visual Quality Preservation of Background
Mahdi Ahmadi, Ali Emami, Mohsen Hajabdollahi +4
By increasing the volume of telemedicine information, the need for medical image compression has become more important. In angiographic images, a small ratio of the entire image us…
Classification of Informative Frames in Colonoscopy Videos Using Convolutional Neural Networks with Binarized Weights
Mojtaba Akbari, Majid Mohrekesh, Shima Rafiei +4
Colorectal cancer is one of the common cancers in the United States. Polyp is one of the main causes of the colonic cancer and early detection of polyps will increase chance of can…