A5032583303- Advanced X-ray and CT Imaging
- Radiation Dose and Imaging
- Medical Imaging Techniques and Applications
- Radiomics and Machine Learning in Medical Imaging
- AI in cancer detection
- Sarcoma Diagnosis and Treatment
- Neuroendocrine Tumor Research Advances
- Cardiac Imaging and Diagnostics
- Colorectal Cancer Screening and Detection
- Adrenal and Paraganglionic Tumors
- Ovarian cancer diagnosis and treatment
- Radiology practices and education
- Lymphoma Diagnosis and Treatment
- Pancreatic and Hepatic Oncology Research
- Photoacoustic and Ultrasonic Imaging
- Intraperitoneal and Appendiceal Malignancies
- Colorectal and Anal Carcinomas
- Soft tissue tumor case studies
- Cardiac tumors and thrombi
- Advanced Radiotherapy Techniques
- Colorectal Cancer Surgical Treatments
- Vascular Tumors and Angiosarcomas
- Advanced MRI Techniques and Applications
- Adrenal Hormones and Disorders
- Pituitary Gland Disorders and Treatments
The University of Texas MD Anderson Cancer Center
2016-2025
National University College
2024
Mayo Clinic in Arizona
2024
New York University
2024
University of Washington
2024
ORCID
2022
General Electric (Israel)
2022
Harborview Medical Center
2021
Mayo Clinic
2021
Toronto General Hospital
2021
OBJECTIVE. The purpose of this study was to perform quantitative and qualitative evaluation a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT the abdomen. MATERIALS AND METHODS. Retrospective review (April-May 2019) cases adults undergoing staging with portal venous phase abdominal conducted for standard 30% adaptive statistical iterative V (30% ASIR-V) compared DLIR at low, medium, high strengths. Attenuation noise measurements were performed. Two...
Iterative reconstruction (IR) algorithms are the most widely used CT noise-reduction method to improve image quality and have greatly facilitated radiation dose reduction within radiology community. Various IR methods different strengths limitations. Because typically nonlinear, they can modify spatial resolution noise texture in regions of image; hence traditional image-quality metrics not appropriate assess ability preserve diagnostic accuracy, especially for low-contrast tasks. In this...
Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate metastases and image quality between reduced-dose reconstruction (DLIR) standard-dose filtered back projection (FBP) contrast-enhanced abdominal CT. Materials Methods In this prospective Health Insurance Portability Accountability Act–compliant study (September 2019 through April 2021), participants with...
Purpose To evaluate colorectal cancer hepatic metastasis detection and characterization between reduced radiation dose (RD) standard (SD) contrast material–enhanced CT of the abdomen to qualitatively compare filtered back projection (FBP) iterative reconstruction algorithms. Materials Methods In this prospective study (from May 2017 through November 2017), 52 adults with biopsy-proven suspected metastases at baseline underwent two portal venous phase scans: SD RD in same breath hold. Three...
Artificial intelligence (AI) is the most revolutionizing development in health care industry current decade, with diagnostic imaging having greatest share such development. Machine learning and deep (DL) are subclasses of AI that show breakthrough performance image analysis. They have become state art field classification recognition. deals extraction important characteristic features from images, whereas DL uses neural networks to solve problems better performance. In this review, we...
The purpose of this study is to evaluate the clinical, pathologic, and multimodality cross-sectional imaging features a cohort 94 patients with desmoplastic small round cell tumor (DSRCT).This retrospective pathologically verified DSRCT was conducted at tertiary cancer center between 2001 2013. Epidemiologic, findings were recorded. Tumor size, location, shape distribution pattern metastases presentation analyzed.DSRCT most often occurred in young (median age, 21.5 years; range, 5-53 years),...
Neurofibromatosis type 1 (NF1) and neurofibromatosis 2 (NF2) are autosomal dominant inherited neurocutaneous disorders or phakomatoses secondary to mutations in the NF1 NF2 tumor suppressor genes, respectively. Although they share a common name, distinct with wide range of multisystem manifestations that include benign malignant tumors. Imaging plays an essential role diagnosis, surveillance, management individuals NF2. Therefore, it is crucial for radiologists be familiar imaging features...
216 Background: Colorectal cancer (CRC) is the second leading cause of cancer-related deaths. We previously found that delayed diagnosis due to lack radiological identification results in significantly worse outcome for patients. had developed a rudimentary, AI observer which demonstrated potential detecting CRC on routine CT abdomen/pelvis (CTAP). However, algorithm detected many false positives. In this study, we analyzed data using TCIA as test cases and evaluated whether patient...
Objective The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction–V (ASIR-V) model-based reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Methods Materials Abdominopelvic scans for 36 patients (26 males 10 females) were using FBP, ASIR (80%), Veo 3.0, ASIR-V (30%, 60%, 90%). Mean ± SD patient age 32 years mean body mass index 26.9 4.4 kg/m 2 . Images reviewed by independent readers...
The purpose of this study was to characterize image quality and dose performance with GE CT iterative reconstruction techniques, adaptive statistical recontruction (ASiR), model-based (MBIR), over a range typical low-dose intervals using the Catphan 600 anthropomorphic Kyoto Kagaku abdomen phantoms. scope project quantitatively describe advantages limitations these approaches. phantom, supplemented fat-equivalent oval ring, scanned Discovery HD750 scanner at 120 kVp, 0.8 s rotation time,...
Abstract Along with the rest of world, United States is inundated by COVID-19 pandemic. The medical services in country have been severely affected. pandemic poses extraordinary challenges to academic institutions including radiology residency and fellowship programs. Herein, we delineate major difficulties faced our training program mitigating countermeasures. primary objective discuss changes programs due allow for continued education.