Prostate: JPC-01K

Prostate: JPC-01K

Prostate Cancer
Prostate cancer detection solution

Description




WHY JPC-01K

  • Providing quantitative analysis result of prostate cancer detection to assist physicians and medical staff in diagnosing prostate cancer
  • Resolves difficulties in MR images analysis, which is highly dependent on the doctor's personal experience
  • Access management to enhance the security of the system
  • Improvement of system performance by constantly reflecting knowledge of experts
  • Convenient patient data management through PACS

Application:

Based on the patient's multiparametric prostate MRI data, the solution automatically analyze the location of prostate cancer tumor & visualize the probability of presence of cancer and to assist diagnosis of prostate cancer location and clinical stage of medical staff clinical stage.

JPC-01K is an AI medical system that detects the area of prostate cancer using multiparametric MR images. The system is based on artificial neural networks to analyze the MR images of the prostate cancer patients. The system uses multiparametric MR images, T2, DWI, and DCE, as input and visualizes the location of the prostate cancer and their probability.

Physicians using our system can diagnose prostate cancer patients faster, more efficiently, and more accurately. JPC-01K is currently classified as ‘Computer Aided Diagnosis Software’ (A26430.14(3)) and has submitted application for large-scale and multi-center clinical trial to the Ministry of Food and Drug Safety in Korea.

Characteristics

  • Auto-detection and visualization of prostate cancer location
  • Semi-automatic MR sequences classification and additional DCE (MaxRelEnh, VE, Wash-In, iAUC) parameters calculation
  • Various image processing tools (panning, zoom-in and out, and change of brightness and contrast), multiplane (axial, coronal, sagittal plane) synchronization, and DWI and DCE temporal data visualization
  • Annotation on the patient's MR images
  • PACS-linked patient data management • Visualization of clinical information • Analysis result report page