Implement comprehensive style consistency updates across MONAI website

Major changes:
- Standardized heading styles across all pages (h1, h2, h3)
- Implemented consistent background color alternation patterns
  - Product pages: 3-color rotation (white → brand-light → neutral-lightgray)
  - Content pages: 2-color alternation (white → neutral-lightgray)
- Removed all dot pattern overlays for cleaner appearance
- Fixed consecutive same-color sections in label.html and deploy.html
- Updated text spacing and typography for consistency
- Standardized card components and hover effects
- Removed deprecated pages: action.html, docs.html, community.html
- Converted started.html to redirect to tutorials.html
- Created comprehensive MONAI_STYLE_GUIDE.md documentation
- Created STYLE_REVIEW_FINDINGS.md with detailed analysis

All pages now follow a cohesive design system that enhances user experience and maintainability.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

Author: Claude Assistant

about.html

@@ -19,19 +19,19 @@
 
   <main class="flex-grow pt-20">
     <!-- About Section -->
-    <section id="about" class="py-24">
+    <section id="about" class="py-24 bg-white">
       <div class="container">
         <div class="flex flex-wrap items-center">
           <div class="w-full lg:w-1/2">
-            <h2 class="mb-6 section-heading">About MONAI</h2>
+            <h1 class="text-4xl font-bold text-gray-800 mb-8">About MONAI</h1>
             <div class="w-full sm:3/5">
-              <p class="py-2">
+              <p class="text-lg leading-relaxed text-gray-700 mb-4">
                 Project MONAI is a collaborative initiative that brings together leading researchers, clinicians, and industry experts 
                 to advance medical imaging AI. Originally started by NVIDIA and King's College London, MONAI has grown into a vibrant 
                 community focused on developing and sharing best practices, tools, and frameworks for healthcare imaging across academia 
                 and enterprise.
               </p>
-              <p class="py-2">
+              <p class="text-lg leading-relaxed text-gray-700 mb-4">
                 Our mission is to accelerate the adoption of AI in healthcare imaging by providing robust, validated tools and fostering 
                 collaboration between researchers, clinicians, and industry partners. Building upon the foundations laid by toolkits like 
                 NVIDIA Clara Train, NiftyNet, DLTK, and DeepNeuro, MONAI Core has emerged as our flagship framework, embodying the 
@@ -47,21 +47,21 @@ <h2 class="mb-6 section-heading">About MONAI</h2>
     </section>
 
     <!-- Advisory Board Section -->
-    <section id="advisory-board" class="py-12 bg-brand-dark/15">
+    <section id="advisory-board" class="py-24 bg-neutral-lightgray ">
       <div class="container">
-        <h2 class="section-heading text-3xl md:text-4xl font-bold mb-4">Advisory Board</h2>
+        <h2 class="text-3xl font-bold text-neutral-darkestblack mb-8">Advisory Board</h2>
         <div class="max-w-4xl mb-12">
-          <p class="text-gray-700 mb-4">
+          <p class="text-lg leading-relaxed text-gray-700 mb-4">
             The MONAI Advisory Board brings together distinguished leaders from academia, healthcare, and industry who guide our 
             strategic direction and ensure alignment with the needs of the medical imaging community. Our board members contribute 
             their diverse expertise to shape MONAI's development and impact in healthcare AI.
           </p>
-          <p class="text-gray-700 mb-4">
+          <p class="text-lg leading-relaxed text-gray-700 mb-4">
             Board members play a crucial role in maintaining MONAI's technical excellence, clinical relevance, and ethical standards. 
             They provide strategic oversight across various aspects including technical development, clinical validation, educational 
             initiatives, and community engagement.
           </p>
-          <p class="text-gray-700 mb-6">
+          <p class="text-lg leading-relaxed text-gray-700 mb-6">
             Through regular collaboration with working groups and the broader community, the Advisory Board ensures that MONAI 
             continues to meet the evolving needs of researchers, clinicians, and industry partners while advancing the field of 
             medical imaging AI.