the United States’s
digital diagnostics industry,
in focus.

Challenges in Computer‑Aided Detection

50.0% of this theme group

Researchers highlight limitations and unresolved issues in current computer‑aided detection and diagnosis systems for imaging.

Computer-aided diagnosis (5) · Medical physics (2)

Evaluation of computer-aided detection and diagnosis systems^a)

Current concepts in computer-aided detection for ct colonography

Segmentation and Diagnosis Difficulties

21.4% of this theme group

Papers point to persistent problems in segmenting images and accurately diagnosing pulmonary nodules.

Segmentation (2) · Computer-aided diagnosis (3)

How AI Can Help in the Diagnostic Dilemma of Pulmonary Nodules

Lung CT Image Classification using Deep Neural Networks for Lung Cancer Detection

Caution on Breast Imaging CAD

53.3% of this theme group

Authors urge careful evaluation of computer‑aided detection performance in digital mammography.

Mammography (7) · Breast cancer (7) · Digital mammography (2) · Computer-aided diagnosis (3)

Computer-aided detection of breast masses depicted on full-field digital mammograms: a performance assessment

Article Commentary: Computer-Aided Detection of Breast Cancer — Have All Bases Been Covered?

Risks in Colonoscopy CAD

26.7% of this theme group

Studies warn about potential pitfalls when applying computer‑aided diagnosis to colonoscopic imaging.

Colonoscopy (3) · Computer-aided diagnosis (3)

Computer-aided diagnosis for colonoscopy

Impact of Original and Artificially Improved Artificial Intelligence–based Computer-aided Diagnosis on Breast US Interpretation

Advances in Breast Imaging Analysis

23.5% of this theme group

Work explores new pattern‑recognition methods for mammography, MRI, and ultrasound to improve breast cancer detection.

Mammography (42) · Breast cancer (28) · Pattern recognition (62) · Breast MRI (12)

Improved Classification of Benign and Malignant Breast Lesions Using Deep Feature Maximum Intensity Projection MRI in Breast Cancer Diagnosi

Presentation of Novel Architecture for Diagnosis and Identifying Breast Cancer Location Based on Ultrasound Images Using Machine Learning

CAD for Radiology Workflow

22.9% of this theme group

Research proposes computer‑aided tools to streamline radiology processes and enhance renal and breast imaging interpretation.

Computer-aided diagnosis (80) · Renal function (7) · Radiology (17) · Workflow (7)

A Computer Aided Diagnosis System in Mammography Using Artificial Neural Networks

Medical imaging and computers in the diagnosis of breast cancer

Lung Nodule Detection Innovations

18.8% of this theme group

Papers present novel deep‑learning techniques for classifying and diagnosing pulmonary nodules on CT scans.

Nodule (25) · Lung cancer (16) · Lung (9) · Computer-aided diagnosis (40)

Computer‐aided diagnosis of pulmonary nodules on CT scans: Improvement of classification performance with nodule surface features

Lung Nodule Diagnosis on 3D Computed Tomography Images Using Deep Convolutional Neural Networks

General Pattern‑Recognition Techniques

17.6% of this theme group

Studies develop convolutional networks and feature extraction methods for diverse segmentation tasks across medical imaging.

Pattern recognition (65) · Segmentation (37) · Convolutional neural network (26) · Feature extraction (14)

Brain Tumor Classification via Statistical Features and Back-Propagation Neural Network

Applying a deep learning based CAD scheme to segment and quantify visceral and subcutaneous fat areas from CT images

False‑Positive Reduction Strategies

7.7% of this theme group

Research focuses on algorithms that lower false‑positive rates in computer‑aided detection of nodules and polyps.

False positive paradox (40) · Computer-aided diagnosis (16) · Software (3) · Nodule (7)

Computer-Aided Tumor Detection Based on Multi-Scale Blob Detection Algorithm in Automated Breast Ultrasound Images

Improved False Positive Reduction by Novel Morphological Features for Computer-Aided Polyp Detection in CT Colonography

Virtual Colonoscopy Enhancements

4.9% of this theme group

Works aim to improve computer‑aided detection in CT colonography through advanced modeling of partial‑volume effects.

Virtual colonoscopy (9) · Computer-aided diagnosis (13) · Colonoscopy (3) · Partial volume (2)

CT colonography: Advanced computer‐aided detection scheme utilizing MTANNs for detection of “missed” polyps in a multicenter clinical trial

Computer-aided detection of colonic polyps with level set-based adaptive convolution in volumetric mucosa to advance CT colonography toward

Prostate Cancer Imaging Advances

4.7% of this theme group

Papers introduce deep‑learning models for grading and diagnosing prostate cancer from MRI data.

Prostate cancer (17) · Prostate (4) · Effective diffusion coefficient (3) · Grading (3)

Classification of clinical significance of MRI prostate findings using 3D convolutional neural networks

A new CNN-based system for early diagnosis of prostate cancer

San Francisco

22.7% across the displayed hubs

21 companies hiring · $6.0B disclosed funding

New York City

21.2% across the displayed hubs

10 companies hiring · $2.4B disclosed funding

San Diego

15.2% across the displayed hubs

7 companies hiring · $4.7B disclosed funding

Boston

10.9% across the displayed hubs

7 companies hiring · $2.1B disclosed funding

Cambridge

8.7% across the displayed hubs

10 companies hiring · $2.2B disclosed funding

Los Angeles

7.5% across the displayed hubs

5 companies hiring · $725.1M disclosed funding

Austin

7.4% across the displayed hubs

9 companies hiring · $1.3B disclosed funding

Irvine

6.4% across the displayed hubs

5 companies hiring · $745.4M disclosed funding