DOI: 10.18710/egrqrc
title: The Prostate_Cancer_CISH_HE_Epithelium_Segmentation dataset

description: &lt;h2&gt;The Prostate_cISH_Epithelium_Segmentation Dataset&lt;/h2&gt;

&lt;p&gt;
 &lt;strong&gt;Corresponding author:&lt;/strong&gt; Henrik Sahlin Pettersen (henrik.s.pettersen@ntnu.no)&lt;br&gt;
 Consultant Pathologist / Associate Professor, St. Olav's Hospital / NTNU, Trondheim, Norway
&lt;/p&gt;

&lt;hr&gt;

&lt;h3&gt;Short Webpage Description&lt;/h3&gt;
&lt;p&gt;
 This dataset provides high-resolution histopathological images and corresponding expert-annotated segmentation masks, specifically designed for developing AI models for prostate epithelium segmentation. The images feature Chromogenic In Situ Hybridization (cISH) staining for various miRNAs, alongside controls and standard Hematoxylin & Eosin (HE) stains. Data originates from 70 patients: 30 with prostate cancer (&lt;strong&gt;PCa&lt;/strong&gt;) and 40 with benign prostatic hyperplasia (&lt;strong&gt;BPH&lt;/strong&gt;).
&lt;/p&gt;

&lt;h3&gt;Sample Collection&lt;/h3&gt;
&lt;ul&gt;
 &lt;li&gt;&lt;strong&gt;Prostate Cancer (PCa):&lt;/strong&gt; 30 patients. Samples include normal glandular epithelium (core type &lt;code&gt;'a'&lt;/code&gt;), Gleason 3 pattern (core type &lt;code&gt;'b'&lt;/code&gt;), and Gleason 4 pattern (core type &lt;code&gt;'c'&lt;/code&gt;), ideally in triplicate for each marker.&lt;/li&gt;
 &lt;li&gt;&lt;strong&gt;Benign Prostatic Hyperplasia (BPH):&lt;/strong&gt; 40 patients. Samples consist of triplicate normal glandular epithelium for each marker.&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Markers and Controls&lt;/h3&gt;
&lt;p&gt;Data is provided for the following stains, each organized into its own top-level folder:&lt;/p&gt;
&lt;ul&gt;
 &lt;li&gt;&lt;strong&gt;miRNAs:&lt;/strong&gt; miR‑550A, miR‑1246, miR‑3614, miR‑4326, miR‑4632, miR‑4742, miR‑4754, miR‑7850&lt;/li&gt;
 &lt;li&gt;&lt;strong&gt;Controls:&lt;/strong&gt; U6 (Positive), Scr (Negative)&lt;/li&gt;
 &lt;li&gt;&lt;strong&gt;Standard Stain:&lt;/strong&gt; Hematoxylin & Eosin (HE)&lt;/li&gt;
&lt;/ul&gt;

&lt;h3&gt;Data Format & Organization&lt;/h3&gt;
&lt;p&gt;
 Each high-resolution image (&lt;code&gt;.jpg&lt;/code&gt;) has a corresponding pixel-level segmentation mask (&lt;code&gt;.png&lt;/code&gt;) delineating the prostate epithelium, suitable for training deep learning models. Segmentation masks are single-channel images where pixel value &lt;strong&gt;0 indicates background&lt;/strong&gt; and pixel value &lt;strong&gt;255 indicates epithelium&lt;/strong&gt;.
&lt;/p&gt;
&lt;p&gt;
 The data is organized first by marker, then by tissue type/origin. Within each marker's top-level folder (e.g., &lt;code&gt;HE/&lt;/code&gt;, &lt;code&gt;550A/&lt;/code&gt;), the structure is:
&lt;/p&gt;
&lt;pre&gt;&lt;code&gt;
[Marker]/
├── Normal/
│ ├── Normal_TURP_BPH/ (Images/masks from BPH patients)
│ └── Normal_Prostatectomy/ (Normal core 'a' images/masks from PCa patients)
└── Cancer/
 └── Cancer_Prostatectomy/ (Gleason 3/4 core 'b'/'c' images/masks from PCa patients)
&lt;/code&gt;&lt;/pre&gt;
&lt;p&gt;
 All image and mask files are located directly within the innermost folders (&lt;code&gt;Normal_TURP_BPH&lt;/code&gt;, &lt;code&gt;Normal_Prostatectomy&lt;/code&gt;, &lt;code&gt;Cancer_Prostatectomy&lt;/code&gt;). Filenames encode marker, patient type, anonymized ID, sample number, core type, and optional experimental details.
&lt;/p&gt;

&lt;h3&gt;Terms of Use&lt;/h3&gt;
&lt;p&gt;
 Distributed under a CC0 license for open research and development.
&lt;/p&gt;