Computational image and molecular analysis reveal unique prognostic features of immune architecture in African Versus European American women with endometrial cancer.

Endometrial cancer (EC) disproportionately affects African American (AA) women in terms of progression and death. In our study, we sought to employ computerized image and bioinformatic analysis to tease out morphologic and molecular differences in EC between AA and European-American (EA) populations. We identified the differences in immune cell spatial patterns between AA and EA populations with markers of tumor biology, including histologic and molecular subtypes.

Opportunistic automated aortic valve calcification assessment in low-cost, screening CT calcium score exams.

Aortic valve stenosis (AS) is the most common valvular disease, with a growing impact in the aging population. AS can culminate in heart failure if left untreated. Early treatment with minimally-invasive transcatheter aortic valve replacement (TAVR) is being evaluated in clinical trials.

Computational image features of immune architecture is associated with clinical benefit and survival in gynecological cancers across treatment modalities.

Background: We present a computational approach (ArcTIL) for quantitative characterization of the architecture of tumor-infiltrating lymphocytes (TILs) and their interplay with cancer cells from digitized H&E-stained histology whole slide images and evaluate its prognostic role in three different gynecological cancer (GC) types and across three different treatment types (platinum, radiation and immunotherapy).

Methods: In this retrospective study, we included 926 patients with GC diagnosed with ovarian cancer (OC), cervical cancer, and endometrial cancer with available digitized diagnostic histology slides and survival outcome information. ArcTIL features quantifying architecture and spatial interplay between immune cells and the rest of nucleated cells (mostly comprised cancer cells) were extracted from the cell cluster graphs of nuclei within the tumor epithelial nests, surrounding stroma and invasive tumor front compartments on H&E-stained slides.

A Generalized Ghost Detection and Segmentation Method for Double-Joint Photographic Experts Group Compression.

Background: The versatility of digital photographs and vast usage of image processing tools have made the image manipulation accessible and ubiquitous. Thus, there is an urgent need to develop digital image forensics tools, specifically for joint photographic experts group (JPEG) format which is the most prevailing format for storing digital photographs. Existing double JPEG methods needs improvement to reduce their sensitivity to the random grid shifts which is highly common in manipulation scenario.