198 citations · 351 across the 25 of their papers we have counts for
26 papers
Deep Learning for Classification of Inflammatory Bowel Disease Activity in Whole Slide Images of Colonic Histopathology
Amit Das, Tanmay Shukla, Naofumi Tomita +4
Grading inflammatory bowel disease (IBD) activity using standardized histopathological scoring systems remains challenging due to resource constraints and inter-observer variabilit…
Masked Pre-Training of Transformers for Histology Image Analysis
Shuai Jiang, Liesbeth Hondelink, Arief A. Suriawinata +1
In digital pathology, whole slide images (WSIs) are widely used for applications such as cancer diagnosis and prognosis prediction. Visual transformer models have recently emerged…
HistoPerm: A Permutation-Based View Generation Approach for Improving Histopathologic Feature Representation Learning
Joseph DiPalma, Lorenzo Torresani, Saeed Hassanpour
Deep learning has been effective for histology image analysis in digital pathology. However, many current deep learning approaches require large, strongly- or weakly-labeled images…
Towards Interpretable Deep Reinforcement Learning Models via Inverse Reinforcement Learning
Sean Xie, Soroush Vosoughi, Saeed Hassanpour
Artificial intelligence, particularly through recent advancements in deep learning, has achieved exceptional performances in many tasks in fields such as natural language processin…
Calibrating Histopathology Image Classifiers using Label Smoothing
Jerry Wei, Lorenzo Torresani, Jason Wei +1
The classification of histopathology images fundamentally differs from traditional image classification tasks because histopathology images naturally exhibit a range of diagnostic…
MHAttnSurv: Multi-Head Attention for Survival Prediction Using Whole-Slide Pathology Images
Shuai Jiang, Arief A. Suriawinata, Saeed Hassanpour
In pathology, whole-slide images (WSI) based survival prediction has attracted increasing interest. However, given the large size of WSIs and the lack of pathologist annotations, e…
Resolution-Based Distillation for Efficient Histology Image Classification
Joseph DiPalma, Arief A. Suriawinata, Laura J. Tafe +2
Developing deep learning models to analyze histology images has been computationally challenging, as the massive size of the images causes excessive strain on all parts of the comp…
A Petri Dish for Histopathology Image Analysis
Jerry Wei, Arief Suriawinata, Bing Ren +9
With the rise of deep learning, there has been increased interest in using neural networks for histopathology image analysis, a field that investigates the properties of biopsy or…
Development and Evaluation of a Deep Neural Network for Histologic Classification of Renal Cell Carcinoma on Biopsy and Surgical Resection Slides
Mengdan Zhu, Bing Ren, Ryland Richards +3
Renal cell carcinoma (RCC) is the most common renal cancer in adults. The histopathologic classification of RCC is essential for diagnosis, prognosis, and management of patients. R…
Sensitivity and Specificity Evaluation of Deep Learning Models for Detection of Pneumoperitoneum on Chest Radiographs
Manu Goyal, Judith Austin-Strohbehn, Sean J. Sun +4
Background: Deep learning has great potential to assist with detecting and triaging critical findings such as pneumoperitoneum on medical images. To be clinically useful, the perfo…
Deep Learning in Diabetic Foot Ulcers Detection: A Comprehensive Evaluation
Moi Hoon Yap, Ryo Hachiuma, Azadeh Alavi +18
There has been a substantial amount of research involving computer methods and technology for the detection and recognition of diabetic foot ulcers (DFUs), but there is a lack of s…
Learn like a Pathologist: Curriculum Learning by Annotator Agreement for Histopathology Image Classification
Jerry Wei, Arief Suriawinata, Bing Ren +10
Applying curriculum learning requires both a range of difficulty in data and a method for determining the difficulty of examples. In many tasks, however, satisfying these requireme…
A Refined Deep Learning Architecture for Diabetic Foot Ulcers Detection
Manu Goyal, Saeed Hassanpour
Diabetic Foot Ulcers (DFU) that affect the lower extremities are a major complication of diabetes. Each year, more than 1 million diabetic patients undergo amputation due to failur…
Multi-Ontology Refined Embeddings (MORE): A Hybrid Multi-Ontology and Corpus-based Semantic Representation for Biomedical Concepts
Steven Jiang, Weiyi Wu, Naofumi Tomita +2
Objective: Currently, a major limitation for natural language processing (NLP) analyses in clinical applications is that a concept can be referenced in various forms across differe…
Difficulty Translation in Histopathology Images
Jerry Wei, Arief Suriawinata, Xiaoying Liu +5
The unique nature of histopathology images opens the door to domain-specific formulations of image translation models. We propose a difficulty translation model that modifies color…
Automatic Post-Stroke Lesion Segmentation on MR Images using 3D Residual Convolutional Neural Network
Naofumi Tomita, Steven Jiang, Matthew E. Maeder +1
In this paper, we demonstrate the feasibility and performance of deep residual neural networks for volumetric segmentation of irreversibly damaged brain tissue lesions on T1-weight…
Predicting colorectal polyp recurrence using time-to-event analysis of medical records
Lia X. Harrington, Jason W. Wei, Arief A. Suriawinata +2
Identifying patient characteristics that influence the rate of colorectal polyp recurrence can provide important insights into which patients are at higher risk for recurrence. We…
Artificial Intelligence-Based Image Classification for Diagnosis of Skin Cancer: Challenges and Opportunities
Manu Goyal, Thomas Knackstedt, Shaofeng Yan +1
Recently, there has been great interest in developing Artificial Intelligence (AI) enabled computer-aided diagnostics solutions for the diagnosis of skin cancer. With the increasin…
Generative Image Translation for Data Augmentation in Colorectal Histopathology Images
Jerry Wei, Arief Suriawinata, Louis Vaickus +4
We present an image translation approach to generate augmented data for mitigating data imbalances in a dataset of histopathology images of colorectal polyps, adenomatous tumors th…
Deep neural networks for automated classification of colorectal polyps on histopathology slides: A multi-institutional evaluation
Jason W. Wei, Arief A. Suriawinata, Louis J. Vaickus +10
Histological classification of colorectal polyps plays a critical role in both screening for colorectal cancer and care of affected patients. An accurate and automated algorithm fo…
Pathologist-level classification of histologic patterns on resected lung adenocarcinoma slides with deep neural networks
Jason W. Wei, Laura J. Tafe, Yevgeniy A. Linnik +3
Classification of histologic patterns in lung adenocarcinoma is critical for determining tumor grade and treatment for patients. However, this task is often challenging due to the…
Automated detection of celiac disease on duodenal biopsy slides: a deep learning approach
Jason W. Wei, Jerry W. Wei, Christopher R. Jackson +3
Celiac disease prevalence and diagnosis have increased substantially in recent years. The current gold standard for celiac disease confirmation is visual examination of duodenal mu…
Attention-Based Deep Neural Networks for Detection of Cancerous and Precancerous Esophagus Tissue on Histopathological Slides
Naofumi Tomita, Behnaz Abdollahi, Jason Wei +3
Deep learning-based methods, such as the sliding window approach for cropped-image classification and heuristic aggregation for whole-slide inference, for analyzing histological pa…
Deep Learning Methods and Applications for Region of Interest Detection in Dermoscopic Images
Manu Goyal, Moi Hoon Yap, Saeed Hassanpour
Rapid growth in the development of medical imaging analysis technology has been propelled by the great interest in improving computer-aided diagnosis and detection (CAD) systems fo…