Merge pull request #11 from ImageMarkup/NickRaymondKurtansky-patch-1

Update index.md with LV reference

index.md

@@ -10,9 +10,11 @@ sub_title: Including the SLICE-3D training dataset - 400,000 skin lesion image c
 
 # Official training and testing datasets of the ISIC 2024 Challenge
 
-The datasets contains 15mm-by-15mm field-of-view cropped images centered on distinct lesions and are extracted from 3D total body photographs. These images are referred to as “tiles.” The official training dataset for the challenge is the SLICE-3D Dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection. The official testing dataset contain tiles from a separate set of patients.
+The training and testing datasets were curated for the [ISIC 2024 Challenge](https://www.kaggle.com/competitions/isic-2024-challenge) hosted on [Kaggle](https://www.kaggle.com/competitions/isic-2024-challenge) during the Summer of 2024.
+
+The datasets contains 15mm-by-15mm field-of-view cropped images, centered on distinct lesions, that were extracted from 3D total body photographs. The official training dataset for the challenge is the SLICE-3D Dataset: 400,000 skin lesion image crops extracted from 3D TBP for skin cancer detection. The official testing dataset contain tiles from a separate set of patients.
 
-All data was curated by the International Skin Imaging Collaboration (ISIC), and images were contributed from the following sources:
+Datasets were curated by the International Skin Imaging Collaboration (ISIC) from images contributed from the following sources:
 + Memorial Sloan Kettering Cancer Center (USA)
 + Hospital Clinic de Barcelona (Spain)
 + The University of Queensland (Australia)
@@ -23,8 +25,6 @@ All data was curated by the International Skin Imaging Collaboration (ISIC), and
 + Alfred Hospital (Australia)
 + FNQH Cairns (Australia)
 
-The training and testing datasets were curated for the [ISIC 2024 Challenge](https://www.kaggle.com/competitions/isic-2024-challenge) hosted on [Kaggle](https://www.kaggle.com/competitions/isic-2024-challenge) during the Summer of 2024.
-
 
 <div class="overflow-x-auto">
 
@@ -116,6 +116,10 @@ The training and testing datasets were curated for the [ISIC 2024 Challenge](htt
 
 </div>
 
+<em>
+    * D’Alessandro, B. "Methods and apparatus for identifying skin features of interest." US Patent #11,164,670. (2021).
+</em>
+
 <h2>Citing 2024 datasets:</h2>
 <h3>SLICE-3D</h3>
 To comply with the attribution requirements of the
@@ -174,7 +178,6 @@ the aggregate "SLICE-3D Permissive" data must be cited as:
       The dataset was generated by the International Skin Imaging Collaboration (ISIC) and images are
       from the following sources: Memorial Sloan Kettering Cancer Center, FNQH Cairns,
       The University of Queensland, Melanoma Institute Australia, and University of Athens Medical School.
-
     </p>
     <p>You should have received a copy of the license along with this work.</p>
     <p>If not, see